Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
This office action is in response to the claims filed on 08/25/2025.
Claims 1-20 are presented for examination.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08/25/2025 has been entered.
Response to Argument
In reference to applicant’s argument regrading rejections under 35 U.S.C. § 101:
Applicant’s Argument:
With respect to step 2A of the patent-eligibility analysis, the Office Action asserts that the steps of Claim 1 are directed to an abstract idea because these steps are assessed to be concepts performed in the human mind. It is respectfully submitted that amended Claim 1 recites "outputting information associated with the ith group of data and the processing results of the ith group of data from the ith nonlocal memory cell to the (i+l)th nonlocal memory cell to process the (j+1)th piece of data," which is not a concept performed in the human mind. To that end, it is respectfully submitted that the claim amendments clarify the non- abstract features of the claimed subject matter. Accordingly, it is respectfully requested that a new patent-eligibility analysis be performed on the amended claims.
Examiner’s Response:
Examiner respectfully disagrees to applicant’s argument since the applicant’s argument does not provide the detail of how the claim limitation is not able to be performed in human mind. Furthermore, a current claim amendment is not overcome the 101 rejection since the claim limitation still recite the mental process, such as ;” “a difference between the second time step and each time step corresponding to a respective piece of data in the ithgroup of data is larger than a threshold.” This is a mental process, the human mind can process the result for the different between the two time step when the I th group of data larger than the threshold, (Observation/Evaluation)
The additional limitations are not integrated into a practical application. The claim does not recite the improvement of the machine learning model or the improvement of function of the computer in the technology field.
As the step 2A prong 2 and step 2B analysis:
The claim 1 recites:
- the N groups of data including N video frame groups when the target sequence data includes target video data, and the N groups of data including N sequential phrases of at least one sentence when the target sequence data includes target text data”, “first time step corresponding to the jth piece of data and a second time step corresponding to the (i+1)th piece of data being adjacent” This/these limitation(s) is/are amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception and that it does not integrate the judicial exception into a practical application.
-“ the ith groupof data corresponding to an ith nonlocal memory cell”, “the N groups of data corresponding to an (i+l)h nonlocal memory cell” These/this limitation(s) are/is recited at a high-level of generality such that it amounts to necessary data storing . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data storing to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
-“wherein the processing includes outputting information associated with the ith group of data” These/this limitation(s) are/is recited at a high-level of generality such that it amounts to necessary data outputting . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data outputting to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
-“and the processing results of the ithgroup of data from the ith nonlocal memory cell to the (i+l)th nonlocal memory cell to process the (j+l)th piece of data” These/this limitation(s) are/is recited at a high-level of generality such that it amounts to necessary data gathering . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gatehring to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
Therefore, the applicant’s argument is not persuasive, the rejection is still maintained.
In reference to applicant’s argument regrading rejections under 35 U.S.C. § 112:
Applicant’s Argument:
The applicant’s argument includes the newly amended limitation filed on 08/25/2025.
Examiner’s Response:
This argument includes the newly amended limitations. It has been fully considered but is moot in view of the new grounds of rejection presented below necessitated by the amendment.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 analysis:
In the instant case, the claims are directed to a method (claims 1-7), apparatus (claims 8-14) and non-transitory computer readable storage medium (claims 15-20). Thus, each of the claims falls within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter).
Step 2A analysis:
Based on the claims being determined to be within of the four categories (Step 1), it must be determined if the claims are directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), in this case the claims fall within the judicial exception of an abstract idea. Specifically the abstract idea of “Mental Processes/Concepts performed in the human mind (including an observation, evaluation, judgment, opinion)” and mathematical concept.
The claim 1 recites :
Step 2A: prong 1 analysis:
-“ A data processing method, comprising: obtaining , and according to an ith group of data in the N groups, processing, and according to (i) processing results for the ith group of data, and a processing result for a jth piece of data in an (i+1)th group of data in the N groups of data, (ii) the ith group of data, and (iii) the processing results of the ith group of data, a (j+1)th piece of data in the (i+1)th group of data” this is a mental process, the human mind can generate/process the result of particular group data (I group data) based on the each subset and/or each piece of data in that particular group based on the data of that group, for example, the human mind can generate the result of location of the person based on received the time series data at the specific location of that particular person, (observation/Evaluation).
-“a difference between the second time step and each time step corresponding to a respective piece of data in the ithgroup of data is larger than a threshold.” This is a mental process, the human mind can process the result for the different between the two time step when the I th group of data larger than the threshold, (Observation/Evaluation)
a) Step 2A: Prong 2 analysis:
-“ comprising: obtaining target sequence data, the target sequence data comprising N groups of data sorted in chronological order, N being greater than 1”, “-“and the processing results of the ithgroup of data from the ith nonlocal memory cell to the (i+l)th nonlocal memory cell to process the (j+l)th piece of data” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data gathering. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gathering to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
- the N groups of data including N video frame groups when the target sequence data includes target video data, and the N groups of data including N sequential phrases of at least one sentence when the target sequence data includes target text data”, “first time step corresponding to the jth piece of data and a second time step corresponding to the (i+1)th piece of data being adjacent” This/these limitation(s) is/are amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception and that it does not integrate the judicial exception into a practical application.
-“ the ith groupof data corresponding to an ith nonlocal memory cell”, “the N groups of data corresponding to an (i+l)h nonlocal memory cell” These/this limitation(s) are/is recited at a high-level of generality such that it amounts to necessary data storing . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data storing to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
-“wherein the processing includes outputting information associated with the ith group of data” These/this limitation(s) are/is recited at a high-level of generality such that it amounts to necessary data outputting . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data outputting to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
-“ by processing circuitry”, “a target neural network model”, “by using the target neural network model” these additional limitations are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (machine learning model, processing circuitry) (See MPEP 2106.05(f)).
b) Step 2B analysis:
-“ obtaining target sequence data, the target sequence data comprising N groups of data sorted in chronological order, N being greater than 1”, “comprising: obtaining target sequence data, the target sequence data comprising N groups of data sorted in chronological order, N being greater than 1”, “-“and the processing results of the ithgroup of data from the ith nonlocal memory cell to the (i+l)th nonlocal memory cell to process the (j+l)th piece of data” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data gathering. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gathering to a judicial exception do not amount to significantly more than the judicial exception itself.
The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
- the N groups of data including N video frame groups when the target sequence data includes target video data, and the N groups of data including N sequential phrases of at least one sentence when the target sequence data includes target text data”, “first time step corresponding to the jth piece of data and a second time step corresponding to the (i+1)th piece of data being adjacent” This/these limitation(s) is/are amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception and that it does not integrate the judicial exception into a practical application.
-“ the ith groupof data corresponding to an ith nonlocal memory cell”, “the N groups of data corresponding to an (i+l)h nonlocal memory cell” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data storing . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data storing to a judicial exception do not amount to significantly more than the judicial exception itself.
The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
-“wherein the processing includes outputting information associated with the ith group of data” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data outputting . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data outputting to a judicial exception do not amount to significantly more than the judicial exception itself.
The courts have similarly found limitations directed to displaying a result, recited at a high level of generality, to be well-understood, routine, and conventional. See (MPEP 2106.05(d)(II), "presenting offers and gathering statistics.", “determining an estimated outcome and setting a price”).
-“ by processing circuitry”, “a target neural network model”, “by using the target neural network model” these additional elements are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (machine learning model, processing circuitry) (See MPEP 2106.05(f)).
The claim 2 recites :
Step 2A: prong 1 analysis:
-“wherein the processing comprises: processing the I th group of data in the N, to obtain second feature information” this is a mental process, the human mind can process the result of the I th group data in the N group of data, for example, the human mind can obtain the feature information (location information) by generating the location information of the person based on the where that person go during a day, , (Observation/Evaluation).
-“ processing the second feature information and third feature information by using a first gate in the target processing model, to obtain first feature information” this is a mental process, the human mind can process the second feature information (location information), where is the store/ restaurant that person shops or eats in the morning to obtain other feature information (shopping/eat habit) , (Observation/Evaluation).
-“ processing, according to the first feature information and the processing result for the jt piece of data in the (i+1)t group of data, the (j+1)th piece of data in the (i+1)th group of data” this is a mental process, the human mind can processing the feature information and processing the result of the j, (j+1) piece data, (Observation/Evaluation).
a) Step 2A: Prong 2 analysis:
-“the target neural network model”, “using a target self-attention model”, “using a first gate in the target processing model”, “ by using the target neural network model.”, the first gate being configured to control a proportion of the second feature information outputted to the first feature information and a proportion of the third feature information outputted to the first feature information;” these additional elements are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (machine learning model, target neural network model, a target self-attention model) (See MPEP 2106.05(f)).
-“ a first gate in the target processing model (i+1)th nonlocal memory cell” These/this limitation(s) are/is recited at a high-level of generality such that it amounts to necessary data storing . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data storing to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
- “and the processing results of the target neural network model for the it group of data by using a target self-attention model in a target processing model, to obtain second feature information”, “the first feature information being intra-group feature information of the (i+1)t group of data, the third feature information being intra-group feature information of the it group of data” This/these additional element(s) is/are amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception and that it does not integrate the judicial exception into a practical application.
b) Step 2B analysis:
-“the target neural network model”, “using a target self-attention model”, “using a first gate in the target processing model”, “ by using the target neural network model.” the first gate being configured to control a proportion of the second feature information outputted to the first feature information and a proportion of the third feature information outputted to the first feature information;” these additional elements are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (machine learning model, target neural network model, a target self-attention model) (See MPEP 2106.05(f)).
“ a first gate in the target processing model (i+1)th nonlocal memory cell” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data storing . As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data storing to a judicial exception do not amount to significantly more than the judicial exception itself.
The courts have similarly found limitations directed to displaying a result, recited at a high level of generality, to be well-understood, routine, and conventional. See (MPEP 2106.05(d)(II), "presenting offers and gathering statistics.", “determining an estimated outcome and setting a price”).
- “and the processing results of the target neural network model for the it group of data by using a target self-attention model in a target processing model, to obtain second feature information”, “the first feature information being intra-group feature information of the (i+1)t group of data, the third feature information being intra-group feature information of the it group of data” This/these additional element(s) is/are amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself.
The claim 3 recites:
Step 2A: prong 1 analysis:
-“ wherein the processing, according to the first feature information and the processing result of the target neural network model for the jth piece of data in the (i+1)th group of data, the (j+1)t piece of data comprises: processing the first feature information and the (j+1)th piece of data in the (i+1)t group of data by using a second gate, to obtain a target parameter,”, “processing the target parameter” this is a mental process, the human mind can process more location information of the person based on the other feature information , for example, where is the person usually go after she/he went to the shopping in the morning, (Observation/Evaluation).
-“ processing the first feature information and the (j+1)th piece of data in the (i+1)t group of data by using a second gate, to obtain a target parameter” this is a mental process, the human mind can process the first information and (j+1) pieces data to obtain the target parameter, (Observation/Evaluation).
a) Step 2A: Prong 2 analysis:
- “ the target neural network model”, “ the second gate being configured to control a proportion of the first feature information outputted to the target parameter and a proportion of the (j+1)t piece of data outputted to the target parameter;”, “by using the target neural network model”, these additional element(s) are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (target neural network model, second gate)) (See MPEP 2106.05(f)).
b) Step 2B analysis:
- “ the target neural network model”, “ the second gate being configured to control a proportion of the first feature information outputted to the target parameter and a proportion of the (j+1)t piece of data outputted to the target parameter;”, “by using the target neural network model”, these additional elements are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (target neural network model, second gate)) (See MPEP 2106.05(f)).
The claim 4 recites :
Step 2A: prong 1 analysis:
a) Step 2A: Prong 2 analysis:
-“ wherein after the target sequence data is obtained, the method further comprises: obtaining the N groups of data according to a target sliding window applied to the target sequence data.” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data gathering. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gathering to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
b) Step 2B analysis:
-“ wherein after the target sequence data is obtained, the method further comprises: obtaining the N groups of data according to a target sliding window applied to the target sequence data.” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data gathering. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gathering to a judicial exception do not amount to significantly more than the judicial exception itself .
The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
The claim 5 recites :
Step 2A: prong 1 analysis:
-“ determining first probability information according to a processing result for at least one video frame in at least one of the N video frame groups” this is a mental process, the human mind can determine the first probability information based on the processing the result the video frame in the N group of the video frame, for example, the human mind can determine the probability location information based on the video about activities of that person(Observation/Evaluation).
-“ determining, according to the first probability information, that the action performed by the target object is a target action in the reference action set.” this is a mental process, the human mind can determine the action performed by the target object based on the probability information, (Observation/Evaluation).
a) Step 2A: Prong 2 analysis:
-“ wherein the target sequence data is target video data, N video frame groups are sorted in chronological order and being used for recognizing an action performed by a target object in the target video data;” , “the first probability information indicating a probability that the action performed by the target object is each reference action in a reference action set” These/this additional element(s) are/is amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception and that it does not integrate the judicial exception into a practical application.
b) Step 2B analysis:
-“ wherein the target sequence data is target video data, the target video data comprising N video frame groups sorted in chronological order and being used for recognizing an action performed by a target object in the target video data;” , “the first probability information indicating a probability that the action performed by the target object is each reference action in a reference action set” These/this additional element(s) are/is amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself.
The claim 6 recites :
Step 2A: prong 1 analysis:
-“determining second probability information according to a processing result for at least one word in at least one of the N sequential phrases” this is a mental process, the human mind can determine the probability information based on the word in the phrases, for example, the human can guess what the next word of other person will say during the conversion(Observation/Evaluation).
-“determining, according to the second probability information, that the sentiment class expressed by the target text data is a target sentiment class in the reference sentiment class set.” this is a mental process, the human mind can determine the sentiment class expressed by the target data based on the probability information, (Observation/Evaluation).
a) Step 2A: Prong 2 analysis:
-“wherein the target sequence data is target text data, and the target text data is used for recognizing a sentiment class expressed by the target text data;”, “ the second probability information indicating a probability that the sentiment class expressed by the target text data is each reference sentiment class in a reference sentiment class set; and determining” These/this additional element(s) are/is amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception and that it does not integrate the judicial exception into a practical application.
b) Step 2B analysis:
-“wherein the target sequence data is target text data, the target text data comprising at least one sentence, the at least one sentence comprising N sequential phrases, and the target text data being used for recognizing a sentiment class expressed by the target text data;”, “ the second probability information indicating a probability that the sentiment class expressed by the target text data is each reference sentiment class in a reference sentiment class set; and determining” This/these additional element(s) is/are amount to no more than generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself.
The claim 7 recites:
-“ and determining a recognition result based on an output result of a last piece of data in the N groups of data that is input into the target neural network model.” this is a mental process, the human mind can determine the recognition result based on the output result of the last piece of the data in N group data, (Observation/Evaluation).
a) Step 2A: Prong 2 analysis:
-“ sequentially inputting each piece of data in the N groups of data into the target neural network model;” These/this additional element(s) are/is recited at a high-level of generality such that it amounts to necessary data gathering. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gathering to a judicial exception do not amount to significantly more than the judicial exception and cannot integrate a judicial exception into a practical application.
-“ the target neural network model” these additional elements are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (target neural network model) (See MPEP 2106.05(f)).
b) Step 2B analysis:
-“ sequentially inputting each piece of data in the N groups of data into the target neural network model;” These/this additional element (s) are/is recited at a high-level of generality such that it amounts to necessary data gathering. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity of data gathering to a judicial exception do not amount to significantly more than the judicial exception itself .
The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
-“ the target neural network model” these additional elements are recited at high level of generality and amounts to no more than mere instructions to apply the judicial exception using a generic computer component (target neural network model) (See MPEP 2106.05(f)).
The claim 8 is rejected for the same reason as the claim 1, since these claims recites the same limitations.
The claim 9 is rejected for the same reason as the claim 2, since these claims recites the same limitations.
The claim 10 is rejected for the same reason as the claim 3, since these claims recites the same limitations.
The claim 11 is rejected for the same reason as the claim 4, since these claims recites the same limitations.
The claim 12 is rejected for the same reason as the claim 5, since these claims recites the same limitations.
The claim 13 is rejected for the same reason as the claim 6, since these claims recites the same limitations.
The claim 14 is rejected for the same reason as the claim 7, since these claims recites the same limitations.
The claim 15 is rejected for the same reason as the claim 1, since these claims recites the same limitations.
The claim 16 is rejected for the same reason as the claim 2, since these claims recites the same limitations.
The claim 17 is rejected for the same reason as the claim 3, since these claims recites the same limitations.
The claim 18 is rejected for the same reason as the claim 4, since these claims recites the same limitations.
The claim 19 is rejected for the same reason as the claim 5, since these claims recites the same limitations.
The claim 20 is rejected for the same reason as the claim 6, since these claims recites the same limitations.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 6, 8, 13, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (Pub. No US20180247126– hereinafter, Li) in view of SETHURAMAN et al (Pub. No. 20170064309-hereinafter, SETHURAMAN) and further in view of Gandhi et al (Pub. No. 20170228614-hereinafter, Gandhi) and further in view of Bellegarda et al (Pub. No. 20200104369 -hereinafter, Bellegarda).
Regrading claim 1, LI teaches data processing method, comprising: obtaining target sequence data (Li, [Par.0009], “The present disclosure provides a method and system for detecting and segmenting primary video objects with neighborhood reversibility”, Examiner’s note, the video data is considered as the target sequence data.),
the target sequence data comprising N groups, N being greater than 1 (Li, [Par.0010], “The present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility” Examiner’s note, each video object is considered as the N group, therefore, the plurality of video objects are considered as the N groups data, and N is greater than 1.);
the N groups of data including N video frame groups when the target sequence data includes target video data (Li, [Par.0010-0011], “The present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u}”).
and obtaining by processing circuitry, according to an ith group of data in the N groups of data (Li, [Par.0010-0011], “The present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u}” Examiner’s note, the video (primary video object) is divided into the plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u}, therefore, the video frames (I.sub.1) data is considered as the I group data. Furthermore, the Par.0025-0027 teaches the feature module obtains and processes the I group data of the N group of data.).
processing results of a target neural network model for the ith group of data (Li, [Par.0010- 0017], “[Par.0010], the present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u} [0017], constructing a deep neural network and predicting an initial foreground value for each super pixel block in each video frame I.sub.u in spatial domain based on the foreground regressor trained and obtained by the deep neural network using a large-scale data set in the field of the image salience;” Examiner’s note, the predicted foreground value for each super pixel block of the video frame (I.sub.1) is considered as the result of the I th group, because the super pixel blocks are divided from the video frame(I.usb.1), and the video frame (I.sub.1) is considered as the I th group data.).
processing, by the processing circuitry and according to (i) a processing result of the target neural network model for a jth piece of data in an (i+l)th group of data in the N groups of data, (ii) the ith group of data, and (iii) the processing results of the ith group of data (Li, [Par.0010- 0017], “[Par.0010], the present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u} [0017], constructing a deep neural network and predicting an initial foreground value for each super pixel block in each video frame I.sub.u in spatial domain based on the foreground regressor trained and obtained by the deep neural network using a large-scale data set in the field of the image salience;” Examiner’s note, the (O.sub.u1) is considered as the j piece data of the video frame (I.sub.2)/(I+1) group data, since the plurality super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u} are divided from the video frame (I.sub.2)/ (I+1) group data. Therefore, the predicted foreground value for each pixel block (O.sub.u1) of the video frame (I.sub.2) by using the deep neural network is considered as the result of the target neural network model for a jth piece of data in an (i+1)th group of data. Each video object (N group data) of the plurality video objects (N group data) is divided into plurality video frames (I.sub.1, I.sub.2, I.sub.3…)/(I, I+1), therefore, the (I, I+1, ) group of data is belong to the N groups of data.),
a (j+1)th piece of data in the (i+1)th group of data by using the target neural network model, to obtain a processing result of the target neural network model for the (j+1)t piece of data in the (i+1)t group of data (Li, [Par.0010- 0017], “[Par.0010], the present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u} [0017], constructing a deep neural network and predicting an initial foreground value for each super pixel block in each video frame I.sub.u in spatial domain based on the foreground regressor trained and obtained by the deep neural network using a large-scale data set in the field of the image salience;” Examiner’s note, the pixel block (O.sub.u2) is considered as the (j+1) piece data of the video frame (I.sub.2)/(I+1) group data, since the plurality super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u} are divided from the video frame (I.sub.2)/ (I+1) group data. Therefore, the predicted foreground value for each pixel block (O.sub.u2) of the video frame (I.sub.2) by using the deep neural network is considered as the result of the target neural network model for a (j+1)th piece of data in an (i+1) th group of data.),
i being greater than or equal to 1 and less than N (Li, [Par.0010-0011]), “[Par.0010], the present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u}” Examiner’s note, the video object (N group data) is divided into plurality of video frames, therefore, each video frame (I.sub.1) or I th group of data is a subset of the video object (N group), therefore, I less than N. The video frame (I.sub.1) or I th group data is the first video frame in the plurality video frames, therefore, I equals 1.),
and j being greater than or equal to 1 and less than Q, Q being a quantity of pieces of data in the (i+1)th group of data (Li, [0011], “dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u}” Examiner’s note, the super pixel block (O.sub.u1) is considered as the j piece data of the video frame(I.sub.2) or (I+1) group data, wherein, video frame (I.sub.2) or (I+1) group data has plurality of the pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u}, therefore, the j or (O.sub.u1) is less than Q (quantity of the pixel blocks (O.sub.u1…O.sub.un)). The pixel block (O.sub.u1) or j data is the first pixel block in the plurality of pixel blocks, therefore, j equals 1.).
a first time step corresponding to the j th piece of data and a second time step corresponding to the (j+1)th piece of data being adjacent, wherein the processing includes outputting information associated with the ith group of data (Li, [Par.0010- 0017], “[Par.0010], the present disclosure provides a method for detecting and segmenting primary video objects with neighborhood reversibility, including: [0011], dividing a pending video to be processed into a plurality of video frames {I.sub.1, I.sub.2, . . . , I.sub.u−1, I.sub.u} and dividing each video frame I.sub.u into a plurality of super pixel blocks {O.sub.u1, O.sub.u2, . . . , O.sub.ui, . . . , O.sub.uN.sub.u} [0017], constructing a deep neural network and predicting an initial foreground value for each super pixel block in each video frame I.sub.u in spatial domain based on the foreground regressor trained and obtained by the deep neural network using a large-scale data set in the field of the image salience;” Examiner’s note, the neural networ predict the each super pixel block in each video frame is corresponding to the output information associated with the Ith group of data (each video frame)
However, Li does not teach N groups of data sorted in chronological order, and the N groups of data including N sequential phrases of at least one sentence when the target sequence data includes target text data, the ith groupof data corresponding to an ith nonlocal memory cell, The (i+l)th group of data in the N groups of data corresponding to an (i+l)th nonlocal memory cell, and the processing results of the ith group of data from the ith nonlocal memory cell to the (i+l)th nonlocal memory cell to process the (j+l)th piece of data, and a difference between the second time step and each time step corresponding to a respective piece of data in the I th group of data is larger than a threshold,
On the other hand, SETHURAMAN teaches N groups of data sorted in chronological order (SETHURAMAN, [Par.0064], “Process 400 then may include “identify picture type of frames” 408, and particularly to identify the I-frames to be intra-coded and to be used as reference frames, the prediction P-frames to be used as reference frames, and the bi-directional B-frames. It is understood that the B-frames could also be used as reference frames, and the processes herein may be adjusted for such a case. For the chronological capture order, this results in captured video sequences that may have an order with a group of pictures (GOP) as used by portable devices such as: IP.sub.1P.sub.2P.sub.3P.sub.4 . . . ; IB.sub.1P.sub.1B.sub.2P.sub.2 . . . ; or IB.sub.1B.sub.2P.sub.1B.sub.3B.sub.4P.sub.2 . . . to provide a few examples.”
Li and SETHURAMAN are analogous in arts because they have the same filed of endeavor of processing the video data by using the machine learning model.
Accordingly, it would have been obvious to one of the ordinary skills in the art before the effective filing date of the claimed invention to modify the obtaining target sequence data, the target sequence data comprising N groups, as taught by Li, to include the N groups of data sorted in chronological order, as taught by SETHURAMAN. The modification would have been obvious because one of the ordinary skills in art would be motivated to save a memory bandwidth, (SETHURAMAN, [Par.0038], “To resolve these issues, the present method of re-ordering frames for video coding may include directly streaming at least one type of picture or frame, such as either B-frames or P-frames, into a display or coding video sequence (or bitstream) for a next video coding task (including transmission to a display) without placing the frames in the off-chip temporary memory. When re-ordering frames from a captured ordered to an encoder order, I and B frames may be written to the off-chip buffer while P-frames are streamed directly to the new video sequence to be encoded and including both the directly streamed frames from the on-chip memory and the frames from the off-chip buffer. Likewise, frames in a decoder order received from a decoder may be re-ordered into a display order by buffering the I and P-frames into the off-chip memory while placing the B-frames into the on-chip memory for direct streaming into the bitstream to display the video. The frames re-ordered by direct streaming rather than buffering to the off-chip memory will provide the savings in memory bandwidth as e