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 .
Claim Objections
Claim 11 is objected to because of the following informalities:
Claim 11 recites “at same times,” but this is grammatically incorrect.
Appropriate correction is required.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Specifically, the title must distinguish from the inventors’ other applications and patents.
The abstract of the disclosure is objected to because it does not “enable the Office and the public generally to determine quickly from a cursory inspection the nature and gist of the technical disclosure.” 37 CFR 1.72(b). Specifically, it is not clear what this technology is used for or what the advantages are.
A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Drawings
Figures 5 and 13 should be designated by a legend such as --Prior Art-- because only that which is old is illustrated. See MPEP § 608.02(g). Fig. 5 appears as Fig. 4B in US20220343112, and Fig. 13 appears as Fig. 19 in the same reference.
Corrected drawings in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. The replacement sheet(s) should be labeled “Replacement Sheet” in the page header (as per 37 CFR 1.84(c)) so as not to obstruct any portion of the drawing figures. If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Information Disclosure Statement
The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered.
Here, specification [0003] refers to a technique that has been proposed, but the technique is not identified.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-15 (all claims) are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of U.S. Pat. App. No. 19/064,978 in view of the prior art as applied below.
Both the pending claims and the conflicting patents are broadly directed to generically processing first and second time series data. Therefore, all of the conflicting patents are directed to the same problem as the present application. Further, any differences between the present claims and the claims in the conflicting patent application are obvious in view of the prior art as applied below. It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the below prior art with the conflicting patent application for implementation details (especially as the patent claims lack implementation details). Based on the findings herein, this is an example of “(A) Combining prior art elements according to known methods to yield predictable results.” MPEP 2143.
This is a provisional nonstatutory double patenting rejection.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-15 (all claims) are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1-15 are rejected for several related reasons. First, the specification asserts that this technology serves to enhance accuracy of inference. See, e.g., specification, [0004], [0011], [0013], and [0015]. However, there is not evidence that the inventor had possession of a version that does not enhance accuracy, even though the claims encompass such a possibility. Limiting the claims to require a (specific) enhancement of accuracy is expected to overcome this issue.
Second, the claims cover a wide array of different implementations, each of which can be thought of as a different specie within the claimed genus. However, the specification only provides details for a small number of possible species. Specifically, specification [0042] and [0072] disclose use of EfficientNet; and specification [0028]-[0029] and [0086] disclose a Spatial Temporal Graph Convolutional Network. The examiner has not identified support for other species. In particular, the examiner has not identified disclosure of what the model 602 is (deep learning is not specific enough to show support).
Lastly, the specification does not evidence that the claimed invention will work for its intended purpose. In order to show possession of a neural network architecture, one of ordinary skill in the art would describe either a new architecture and discuss how it is trained, or point to a known architecture. However, because deep learning is less predictable than traditional software, one of ordinary skill in the art would expect to see performance results to know whether the architecture will work for its intended purpose.
MPEP 2163 (II)(A)(3)(a) states:
An adequate written description of the invention may be shown by any description of sufficient, relevant, identifying characteristics so long as a person skilled in the art would recognize that the inventor had possession of the claimed invention.
…
Estee Lauder Inc. v. L’Oreal, S.A., 129 F.3d 588, 593, 44 USPQ2d 1610, 1614 (Fed. Cir. 1997) (“[A] reduction to practice does not occur until the inventor has determined that the invention will work for its intended purpose.”); Mahurkar v. C.R. Bard, Inc., 79 F.3d 1572, 1578, 38 USPQ2d 1288, 1291 (Fed. Cir. 1996) (determining that the invention will work for its intended purpose may require testing depending on the character of the invention and the problem it solves)
Because the specification is silent on any performance information, it does not appear that the inventor has determined whether this invention will work for its intended purpose. Further, this performance information is also an identifying characteristic.
Further still, claim 13 and specification [0009] recite various types of data that could be used. However, the specification does not have discussion of how well any of these perform, another required identifying characteristic.
Claims 1-3, 5, 6, 14, and 15 recite performing various inferences, but each of these are unlimited functional claiming because of the wide variety of ways that inference can be performed. MPEP 2173.05(g). Specifying a particular neural network architecture, such as EfficientNet, overcomes this rejection.
Claims 1, 6, 14, and 15 recite performing various training, and this raises the same issue as inferring, above.
Claim 13 recites a series joined by “and.” MPEP 2111.01(II) cites Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004), which held that “and” means one of each item in the list (i.e., conjunctive). However, the specification only supports using these individually (i.e., disjunctive). Amending the claim to recite “or” overcomes this issue.
Dependent claims are likewise rejected.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-15 (all claims) are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 14, and 15 twice recite “types … being different from each other,” but “different” is a relative term. MPEP 2173.05(b)(IV). In particular, it is unclear if different “types” refers to the types listed in specification [0009] or simply having different frame rates, as per specification [0021].
Additionally, the claim makes contradictory recitations that the first and second types are both different from each other and internally different because being internally different prevents a comparison between the first and second series.
Further, it is unclear how to determine whether data is “time-series data” if the data has different types.
Claims 1, 14, and 15 recite “calculating … a degree of attention indicating a degree at which attention is given.” However, determining how much attention is given is not generally understood as a calculation, rather it is retrieval.
Claims 1, 5, 14, and 15 recite “each of a plurality of first frames,” but it is unclear how to determine “each” without a precise definition of which frames are in the plurality.
Claims 1, 14, and 15 recite “second frames,” but this lacks sufficient antecedent basis because the claim does not specify that the frames are of the time series data. MPEP 2173.05(e).
Claims 1, 14, and 15 recite “a degree of attention indicating a degree at which attention is given,” but “indicating” is a subjective term because people can differ as to whether something is “indicated” or not. MPEP 2173.05(b)(IV). Reciting an objective standard, such as “is,” overcomes this rejection.
Claims 1, 14, and 15 recite “inference performed by a first model” but it is unclear if this is a required step or if it should instead be interpreted as product-by-process.
Claims 1, 14, and 15 recite “training-inference” but this is new terminology because training and inference are different. MPEP 2173.05(a).
Claims 1, 14, and 15 twice recite “information based on,” but it is unclear how to determine whether information is “based on” other information or not.
Claims 1-3, 5, 14, and 15 repeatedly recite “the inference,” but this lacks sufficient antecedent basis because A) the inferences are recited as being performed by different models and B) what the second model is inferring is unspecified. MPEP 2173.05(e).
Claim 2 recites “wherein the first model is configured to receive input of the first time-series data,” but it is unclear how to determine if a model is configured to receive unspecified data.
Claim 2 twice recites “feature indicating a feature,” but is subjective. MPEP 2173.05(b)(IV). Removing the words “indicating a feature” overcomes this rejection.
Claim 3 twice recites “result representing a result,” and this raises the same issue as above.
Claim 3 recites “configured to receive input of the selected N number of second frames,” but N is not known prior to operation of the claimed steps (see claim 1).
Claim 5 recites “a degree of attention in a temporal axis,” but the plain meaning is unclear. It appears that the intent is the amount of attention at a given time (e.g., figure 5).
Claim 6 recites “the training-inferencing,” but this lacks sufficient antecedent basis (note the “ing” at the end). MPEP 2173.05(e).
Additionally, “training-inferencing” is new terminology. MPEP 2173.05(a).
Claim 6 recites “performing training of the first model along with the training of the second model,” but it is unclear what it means for two trainings to be “along with” each other.
Claim 6 recites “when training,” but this lacks sufficient antecedent basis. MPEP 2173.05(e). In particular, is this any training or all training?
Claim 8 recites “wherein the selecting includes,” but then recites limitations without a clear connection to the antecedent “selecting” in claim 1. For example, is claim 8 requiring N be at least 2 because it recites multiple frames?
Claims 8, 10, and 11 recite “same time,” but this is a relative term without sufficient guidance. MPEP 2173.05(b). Additionally, it is unclear if the intent is that the selection happens at the same time or if the frames are of the same time.
Claim 10 recites “corresponds,” but is subjective. MPEP 2173.05(b)(IV). Removing the words “corresponds to a degree of attention that” overcomes this rejection.
Claim 10 recites “the total degree of attention being calculated based on the two or more degrees of attention,” but this is unclear because “total” and “based on” conflict (because total is addition, but based on is broader).
Claim 10 is also unclear as to whether the total attention is of the selected frame or the two or more pieces of data.
Claim 11 recites selecting “an N number of first frames,” but it is unclear what this means given that the frames are never used.
Claims 12 recites “output-controlling,” but this is new terminology. MPEP 2173.05(a).
Dependent claims are likewise rejected.
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 1-15 (all claims) are rejected under 35 U.S.C. 101 because the claimed invention is not supported by either a credible asserted utility or a well-established utility.
The issue is that the scope of the claims is very broad. See, e.g., specification [0008] “Herein, the inference applicable in the embodiments described below is not limited to the estimation of the behavior of a person, and it is possible to apply any type of inference performed using time-series data.” The asserted utility is an improvement in accuracy. See, e.g., specification, [0004] “If the inference is performed using a plurality of types of time-series data, it is expected to have an enhancement in the accuracy of the inference.” However, it is not credible that this is true for all types of inference and all types of time-series data.
Claims 1-15 (all claims) are also rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. Specifically, because the claimed invention is not supported by either a credible asserted utility or a well-established utility for the reasons set forth above, one skilled in the art clearly would not know how to use the claimed invention.
One way to overcome these rejections is to limit the claim to the particular situation where accuracy is improved. The examiner’s review of the specification has not identified a specific example.
Claims 1-20 (all claims) are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (mental process) without significantly more.
Step 1:
Claim 1 (and its dependents) recite a system, and machines satisfy Step 1 of the eligibility test.
Claim 14 recites a computer program product having a non-transitory computer readable medium, and manufactures satisfy Step 1 of the eligibility test.
Claim 15 recites a method, and processes satisfy Step 1 of the eligibility test.
Step 2A, prong one: All of the elements of the claims are a mental process because a person can look and listen and decide what to pay attention to. Further, the various models are also mental processes, see example 47, claim 2, element (d) (from the July 2024 AI subject matter eligibility examples). MPEP 2106.04(a)(2)(III)(C) explains that use of a generic computer or in a computer environment is still a mental process. In particular, this section begins by citing Gottschalk v. Benson, 409 US 63 (1972). “The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea.” In Benson the Supreme Court did not separately analyze the computer hardware at issue; the specifics of what hardware was claimed is only included in an appendix to the decision.
Because there are no additional elements, no further analysis is required for Step 2A, prong two or Step 2B.
Claim Interpretation
The broadest reasonable interpretation of claim 1’s “hardware processors configured to perform” includes a processor capable of, rather than paired with memory storing instructions. In re Blue Buffalo (Fed. Cir. January 14, 2026, non-precedential, slip opinion retrieved from https://www.cafc.uscourts.gov/opinions-orders/24-1611.OPINION.1-14-2026_2632686.pdf
In the interest of compact prosecution, the claim elements have been mapped.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-15 (all claims) are rejected under 35 U.S.C. 102(a)(1) and/or (a)(2) as being anticipated by US20220343112A1 (“Tani”). References are listed in the Notice of Cited References when they were first cited. If a reference is not identifiable (e.g., due to a typo), it can be identified by searching for the quoted text.
1. An information processing device comprising one or more hardware processors configured to perform:
obtaining one or more pieces of first time-series data and (Tani, abstract, “The acquisition unit acquires sequence data including a plurality of frames”)
one or more pieces of second time-series data, (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
types of the one or more pieces of first time-series data being different from each other, types of the one or more pieces of second time-series data being different from the types of the one or more pieces of first time-series data and being different from each other; (Tani’s frames are different from Tani’s attention levels)
calculating, regarding each of a plurality of first frames included in the first time-series data, a degree of attention indicating a degree at which attention is given in inference performed by a first model configured to receive input of the first time-series data and perform the inference; (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
selecting, from the second time-series data, an N number of second frames using the degree of attention, N being an integer equal to or greater than 1; and (Tani, abstract, “The selection unit selects one or a plurality of frames included in the sequence data as a learning frame to be used for learning data based on the attention level.” See also Figs. 4A-4D. Figs. 4A-4D teach the claimed selecting from the second time series data (i.e., the attention level))
performing training-inference including performing training of a second model configured to perform the inference or performing the inference by the second model using information based on the first time-series data and information based on the selected N number of second frames. (Tani, [0101], “the learning data generation device 10A of the present embodiment can provide learning data applicable to learning models used in various environments”)
2. The device according to claim 1, wherein the first model is configured to receive input of the first time-series data and output, as a result of the inference, a first feature indicating a feature of the first time-series data, and (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
the second model is configured to receive input of the first feature and a second feature indicating a feature of the N number of second frames, and output a result of the inference. (Tani, [0101], “the learning data generation device 10A of the present embodiment can provide learning data applicable to learning models used in various environments”)
3. The device according to claim 1, wherein the second model is configured to:
receive input of a first inference result representing a result of the inference output by the first model, and (Tani, [0101], “the learning data generation device 10A of the present embodiment can provide learning data applicable to learning models used in various environments”)
a second inference result representing a result of the inference performed by a third model configured to receive input of the selected N number of second frames and perform the inference; and (Tani, [0051] “For example, the external information processing device may measure acceleration of a target included in a still image by using a well-known image processing technique or the like” Tani’s well-known information processing technique to measure acceleration from an image teaches the claimed inference by a third model (e.g., the acceleration is inferred).)
output a result of the inference. (Tani, [0101], “the learning data generation device 10A of the present embodiment can provide learning data applicable to learning models used in various environments” Tani’s “used” teaches the claimed inference.)
4. The device according to claim 1, wherein the first time-series data and the second time-series data have a same start time and a same end time. (Tani, Fig. 4A)
5. The device according to claim 1, wherein the first model is a model configured to, regarding each of the plurality of first frames, output a result of the inference including a degree of attention in a temporal axis, and (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
the calculating includes calculating the degree of attention in the temporal axis using the first model. (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
6. The device according to claim 5, wherein the performing the training-inferencing includes performing training of the first model along with the training of the second model; and (Tani describes both models as “trained”)
when training is perform in the training-inference, the calculating includes calculating the degree of attention in the temporal axis using the first model that is being trained along with the second model. (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
7. The device according to claim 1, wherein the second time-series data has a greater amount of data than an amount of data of the first time-series data. (The claimed amount of first time-series data can be arbitrarily chosen such that this limitation is met, e.g., choosing a small amount of the first time-series data)
8. The device according to claim 1, wherein the selecting includes selecting a second frame at a same time as a first frame that has a highest degree of attention among the plurality of first frames. (Tani, Figs. 4A-4D)
9. The device according to claim 1, wherein the obtaining includes obtaining two or more pieces of second time-series data, and (Tani, abstract, “The selection unit selects one or a plurality of frames included in the sequence data as a learning frame to be used for learning data based on the attention level.” See also Figs. 4A-4D. Figs. 4A-4D teach the claimed selecting from the second time series data (i.e., the attention level))
the selecting includes selecting the N number of second frames from each of the two or more pieces of second time-series data. (Tani, abstract, “The selection unit selects one or a plurality of frames included in the sequence data as a learning frame to be used for learning data based on the attention level.” See also Figs. 4A-4D. Figs. 4A-4D teach the claimed selecting from the second time series data (i.e., the attention level))
10. The device according to claim 1, wherein the obtaining includes obtaining two or more pieces of first time-series data, the calculating includes calculating the degree of attention for each of the two or more pieces of first time-series data, and (Tani, abstract, “The attention level derivation unit derives an attention level that is feature data in a time axis direction of each of the plurality of frames included in the sequence data by using a trained model.”)
the selecting includes selecting a second frame at a same time as a first frame that corresponds to a degree of attention that is largest from among two or more degrees of attention calculated regarding the two or more pieces of first time-series data, or (Tani, Figs. 4A and 4B)
selecting a second frame at a same time as a first frame having a total degree of attention that is largest, the total degree of attention being calculated based on the two or more degrees of attention calculated regarding the two or more pieces of first time-series data. (Tani, Figs. 4A and 4B)
11. The device according to claim 1, wherein the selecting includes selecting the N number of second frames at same times as an N number of first frames that, from among the plurality of first frames, have degrees of attention that are equal to local maximum values. (Tani, abstract, “The selection unit selects one or a plurality of frames included in the sequence data as a learning frame to be used for learning data based on the attention level.” See also Figs. 4A-4D. Figs. 4A-4D teach the claimed selecting from the second time series data (i.e., the attention level))
12. The device according to claim 1, wherein the one or more hardware processors are configured to further perform executing output-controlling including outputting the selected N number of second frames. (Tani, abstract, “The selection unit selects one or a plurality of frames included in the sequence data as a learning frame to be used for learning data based on the attention level.” See also Figs. 4A-4D. Figs. 4A-4D teach the claimed selecting from the second time series data (i.e., the attention level))
13. The device according to claim 1, wherein frames included in the first time-series data and frames included in the second time-series data represent one of color image data, skeleton data, optical flow data, depth image data, regional division image data, infrared image data, audio data, and X-ray image data. (Tani, claim 14)
Claim 14 is rejected as per claim 1. See also, Tani, claim 17, teaching the claimed computer program.
Claim 15 is rejected as per claim 1.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See the Agarwal reference from the Japanese Office Action (IDS of July 14, 2026). Additional references are unable to be provided given the above 112 rejections.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID ORANGE whose telephone number is (571)270-1799. The examiner can normally be reached Mon-Fri, 9-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Gregory Morse can be reached at 571-272-3838. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/DAVID ORANGE/ Primary Examiner, Art Unit 2663
Prosecution Insights