DETAILED ACTION
This action is in response to the application filed 07/21/2022. Claims 1-17 are pending and have been examined.
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 .
Specification
The disclosure is objected to because of the following informalities:
On page 3, paragraph 0009, “may cause a large difference in performance the model depending on the amount and quality of learning data used in learning” should read “may cause a large different in the performance of the model depending on the amount and quality of learning data used in learning”.
On page 7, paragraph 0025, “G: y of GB information (x, y, z) of pixel information, B: z of GB information (x, y, z) of pixel information” should read “G: y of RGB information (x, y, z) of pixel information, B: z of RGB information (x, y, z) of pixel information”.
On page 23, paragraph 0084, “s pace” should read “space”.
On page 28, paragraph 00107, “G: y of GB information (x, y, z) of pixel information, B: z of GB information (x, y, z) of pixel information” should read “G: y of RGB information (x, y, z) of pixel information, B: z of RGB information (x, y, z) of pixel information”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
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 1-17 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.
Claim 1 recites the limitation "labeling a first class specifying the first object image in the bounding box" in lines 12-13. It is unclear as to whether the invention is labeling a first class or if the invention is labeling the first object image with the first class. For examination purposes, Examiner has interpreted this to be labeling a first object image with the first class.
Claim 1 recites the limitation "generating a model for determining a class" in lines 19-20. It is unclear as to whether this model is the same model as previously recited in line 14. For examination purposes, Examiner has interpreted this to be the same model.
Claim 1 recites the limitation "the primarily learned model" in lines 21-22. There is insufficient antecedent basis for this limitation in the claim. It is unclear if this is referring to the generated model or if this is referring to primarily learning a weight of a model. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 1 recites the limitation "by the model" in line 23. There is insufficient antecedent basis for this limitation in the claim. It is unclear which model this is referring to. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 1 recites the limitation "labeling the bounding box specifying a second object image" in lines 22-23. There is insufficient antecedent basis for this limitation in the claim. The bounding box was previously used with the first object image. Therefore, it is unclear as to whether this is a new bounding box or the same bounding box. For examination purposes, Examiner interprets this to be a new bounding box.
Claim 1 recites the limitation "labeling …a second class determined with respect to the second object image by the model" in lines 23-24. It is unclear as to whether the invention is labeling a second class or if the invention is labeling the second object image with the second class. For examination purposes, Examiner has interpreted this to be labeling a second object image with the second class.
Claim 1 recites the limitation "by the model" in line 24. There is insufficient antecedent basis for this limitation in the claim. It is unclear which model this is referring to. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 1 recites the limitation "generating a model for secondarily learning the weight of the model based on the second space image" in lines 26-27. It is unclear as to whether this model is the same model as a previously recited model or if this is referring to a new model. For examination purposes, Examiner has interpreted this to be the same model.
Regarding claims 2-15, claims 2-15 are rejected for at least the same reasons as claim 1 since claims 2-15 depend on claim 1.
Claim 2 recites the limitation "labeling the first class to the bounding box" in lines 7-8. It is unclear as to whether the invention is labeling the first class or if the invention is labeling the bounding box. Additionally, claim 1 claimed “labeling a first class specifying the first object image in the bounding box.” It is unclear as to whether this invention is labeling the first class, labeling the first object image, or labeling the bounding box. For examination purposes, Examiner has interpreted this to be labeling a first object image with the first class.
Claim 3 recites the limitation "secondarily learning a weight of a model" in line 3-4. It is unclear as to whether this model is the same model as a previously recited model or if this is referring to a new model. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 3 recites the limitation "generating a model for determining a class" in line 8. It is unclear as to whether this model is the same model as a previously recited model or if this is referring to a new model. For examination purposes, Examiner has interpreted this to be the same model.
Claim 4 recites the limitation "labeling of the second space image" in line 2. There is insufficient antecedent basis for this limitation in the claim. Claim 1 recites “labeling …a second class determined with respect to the second object image by the model.” It is unclear as to what is being labeled. For examination purposes, Examiner has interpreted this to be labeling a second object image with the second class.
Claim 4 recites the limitation "the primarily learned model" in lines 3-4. There is insufficient antecedent basis for this limitation in the claim. It is unclear if this is referring to the generated model or if this is referring to primarily learning a weight of a model. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 4 recites the limitation "by the model" in line 5. There is insufficient antecedent basis for this limitation in the claim. It is unclear which model this is referring to. For examination purposes, Examiner interprets this to be referring to the generated model.
Regarding claim 6, The term “a greater element value” in line 5 is a relative term which renders the claim indefinite. The term “greater” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The element value has been rendered indefinite by the term “greater”.
Regarding claim 6, The term “a smaller element value” in lines 6-7 is a relative term which renders the claim indefinite. The term “smaller” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The element value has been rendered indefinite by the term “smaller”.
Claim 6 recites the limitation "an element value (x,y,z)" in line 7. It is unclear if this is the same as a previously recited element value or if it’s new element value. Additionally, it is unclear as to whether each element value comprises (x,y,z) RGB information or if it is only for this particular instance of element value. For examination purposes, Examiner interprets this to be describing each previously recited element value.
Claim 7 recites the limitation "pixel information" in line 7. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 7 recites the limitation "pixel information" in line 9. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 8 recites the limitation "pixel information" in line 7. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 8 recites the limitation "GB information (x,y,z)" in line 8. It is unclear if this GB information is the same as RGB information in line 7. For examination purposes, Examiner interprets this to be to be the same.
Claim 8 recites the limitation "pixel information" in line 8. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 8 recites the limitation "GB information (x,y,z)" in line 9. It is unclear if this GB information is the same as RGB information in line 7. For examination purposes, Examiner interprets this to be to be the same.
Claim 8 recites the limitation "pixel information" in line 9. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 8 recites the limitation "pixel information" in line 10. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 9 recites the limitation "pixel information" in line 7. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 9 recites the limitation "pixel information" in line 9. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 9 recites the limitation "R: x’ of (x’, y’, z’) of dst(I) acquired from Equation 4" in line 12. It is unclear how dst(I) is acquired from Equation 4. Therefore, it is unclear if this is the same dst(I) as recited in Equation 3. For examination purposes, Examiner interprets this dst(I) to be acquired from Equation 3.
Claim 9 recites the limitation "G: y’ of (x’, y’, z’) of dst(I) acquired from Equation 4" in line 13. It is unclear how dst(I) is acquired from Equation 4. Therefore, it is unclear if this is the same dst(I) as recited in Equation 3. For examination purposes, Examiner interprets this dst(I) to be acquired from Equation 3.
Claim 9 recites the limitation "B: z’ of (x’, y’, z’) of dst(I) acquired from Equation 4" in line 13-14. It is unclear how dst(I) is acquired from Equation 4. Therefore, it is unclear if this is the same dst(I) as recited in Equation 3. For examination purposes, Examiner interprets this dst(I) to be acquired from Equation 3.
Claim 9 recites the limitation "pixel information" in line 15. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 10 recites the limitation "pixel information" in line 15. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 11 recites the limitation "pixel information" in line 4. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 11 recites the limitation "pixel information" in line 8. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 11 recites the limitation "pixel information" in line 10. It is unclear if this is the same pixel information as recited in claim 1 or if it’s new pixel information. For examination purposes, Examiner interprets this to be the same pixel information.
Claim 12 recites the limitation "pixels" in line 10. It is unclear if this is the same the plurality of pixels or if this is a different set of pixels. For examination purposes, Examiner interprets this to be the same set of pixels.
Regarding claim 13, where applicant acts as his or her own lexicographer to specifically define a term of a claim contrary to its ordinary meaning, the written description must clearly redefine the claim term and set forth the uncommon definition so as to put one reasonably skilled in the art on notice that the applicant intended to so redefine that claim term. Process Control Corp. v. HydReclaim Corp., 190 F.3d 1350, 1357, 52 USPQ2d 1029, 1033 (Fed. Cir. 1999). The term “a standard Gaussian normal distribution” in claim 13 is used by the claim to mean “a standard Gaussian normal distribution with…a standard deviation of 100,” while the accepted meaning is “a standard normal distribution with a standard deviation of 1.” The term is indefinite because the specification does not clearly redefine the term.
Claim 13 recites the limitation "as much as a number of all pixels included in the first space image" in line 5-6. It is unclear as to which value is as much as a number of all pixels when the average value is 0 and the standard deviation is 100. For examination purposes, Examiner interprets this to mean that the amount of pixels in the space image must be greater than the standard deviation.
Claim 13 recites the limitation "to each of the all pixels" in line 8. It is unclear how whether this means “to each of the pixels”, “to all pixels”, or a different interpretation. For examination purposes, Examiner interprets this to mean “to each of the pixels”.
Claim 14 recites the limitation "generating the model" in line 23. There is insufficient antecedent basis for this limitation in the claim. It is unclear which model this is referring to. For examination purposes, Examiner interprets this to be referring to the generated model of claim 1.
Claim 14 recites the limitation "a neural network" in line 8. It is unclear as to whether this is the same neural network as claimed in line 4, or if this is a different neural network. For examination purposes, Examiner interprets this to be the same neural network.
Claim 14 recites the limitation "the input space image" in line 10. There is insufficient antecedent basis for this limitation in the claim. It is unclear as to whether this is referring to the space image set to an input layer in line 3 or if this is referring to another input space image. For examination purposes, Examiner interprets this to be the space image set to an input layer.
Claim 14 recites the limitation "a class of the object" in line 11. It is unclear as to whether this is referring to the same class in line 7 or if this is referring to another class. For examination purposes, Examiner interprets this to be the same class as in line 7.
Claim 16 recites the limitation "labeling a first class specifying the first object image in the bounding box" in lines 7-8. It is unclear as to whether the invention is labeling a first class or if the invention is labeling the first object image with the first class. For examination purposes, Examiner has interpreted this to be labeling a first object image with the first class.
Claim 16 recites the limitation "generating a model for determining a class" in lines 14-15. It is unclear as to whether this model is the same model as previously recited in line 9. For examination purposes, Examiner has interpreted this to be the same model.
Claim 16 recites the limitation "the primarily learned model" in lines 16-17. There is insufficient antecedent basis for this limitation in the claim. It is unclear if this is referring to the generated model or if this is referring to primarily learning a weight of a model. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 16 recites the limitation "by the model" in line 18. There is insufficient antecedent basis for this limitation in the claim. It is unclear which model this is referring to. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 16 recites the limitation "labeling the bounding box specifying a second object image" in lines 17-18. There is insufficient antecedent basis for this limitation in the claim. The bounding box was previously used with the first object image. Therefore, it is unclear as to whether this is a new bounding box or the same bounding box. For examination purposes, Examiner interprets this to be a new bounding box.
Claim 16 recites the limitation "labeling …a second class determined with respect to the second object image by the model" in lines 17-19. It is unclear as to whether the invention is labeling a second class or if the invention is labeling the second object image with the second class. For examination purposes, Examiner has interpreted this to be labeling a second object image with the second class.
Claim 16 recites the limitation "by the model" in line 19. There is insufficient antecedent basis for this limitation in the claim. It is unclear which model this is referring to. For examination purposes, Examiner interprets this to be referring to the generated model.
Claim 16 recites the limitation "generating a model for secondarily learning the weight of the model based on the second space image" in lines 21-22. It is unclear as to whether this model is the same model as a previously recited model or if this is referring to a new model. For examination purposes, Examiner has interpreted this to be the same model.
Regarding claim 17, claim 17 is rejected for at least the same reasons as claim 16 since claim 17 depends on claim 16.
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.
Claim 17 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim is directed to a computer readable medium (e.g. see claim 17, line 1), which includes a signal based on the broadest reasonable interpretation (i.e. The ordinary and customary meaning of a computer readable medium that includes signals per se). While the Specification discloses a computer readable memory (see page 37), the Specification is not limiting the computer readable medium to only a non-transitory embodiment. A computer readable medium, or the like, that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments to avoid a rejection under 35 U.S.C 101 by adding the limitation “non-transitory” to the claim and positively reciting that the computer readable medium is a non-transitory computer readable medium. See also In re Nuijten, 500 F.3d 1346, 1356-57 (Fed. Dir. 2007) (transitory embodiments are not directed to statutory subject matter). Examiner notes that if Applicant amends to overcome the signals per se rejection, claim 17 will still be rejected under 35 U.S.C. 101.
Claims 1-17 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
Subject Matter Eligibility Analysis Step 1:
Claim 1 recites a data augmentation-based object analysis model learning apparatus and is thus a machine, one of the four statutory categories of patentable subject matter.
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 1 recites
Generating a second space image by changing pixel information included in the first space image (This limitation is a mental process as it encompasses a human mentally creating a second image by changing pixel information.)
specifying a bounding box in a region including the first object image in the first space image (This limitation is a mental process as it encompasses a human mentally specifying a bounding box.)
labeling a first class specifying the first object image in the bounding box (This limitation is a mental process as it encompasses a human mentally labeling the first object.)
determining a class (This limitation is a mental process as it encompasses a human mentally determining a class.)
labeling the bounding box specifying a second object image in the second space image by the model and a second class determined with respect to the second object image by the model, to the second space image (This limitation is a mental process as it encompasses a human mentally label the bounding box.)
Therefore, claim 1 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 1 further recites additional elements of
A data augmentation-based object analysis model learning apparatus comprising: one or more memories configured to store instructions for performing a predetermined operation; and one or more processors operatively connected to one or more memories and configured to execute the instructions (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Acquiring a first space image including a first object image (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Primarily learning a weight of a model designed based on a predetermined object detection algorithm, for deriving a correlation between the first object image in the bounding box and the first class (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Inputting the first space image to the model (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Generating a model for determining a class (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Inputting the second space image to the primarily learned model (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Generating a model for secondarily learning the weight of the model based on the second space image (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Therefore, claim 1 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 1 do not provide significantly more than the abstract idea itself, taken alone and in combination because
A data augmentation-based object analysis model learning apparatus comprising: one or more memories configured to store instructions for performing a predetermined operation; and one or more processors operatively connected to one or more memories and configured to execute the instructions uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Acquiring a first space image including a first object image is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
Primarily learning a weight of a model designed based on a predetermined object detection algorithm, for deriving a correlation between the first object image in the bounding box and the first class uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Inputting the first space image to the model is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
Generating a model for determining a class uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Inputting the second space image to the primarily learned model is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
Generating a model for secondarily learning the weight of the model based on the second space image uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Therefore, claim 1 is subject-matter ineligible.
Regarding Claim 2:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 2 recites
The operation further includes generating a set for storing a plurality of classes specifying object information (This limitation is a mental process as it encompasses a human mentally generating a set for storing a plurality of classes.)
Labeling the first class to the bounding box when a bounding box is specified in a region of the first object image in the first space image (This limitation is a mental process as it encompasses a human mentally labeling the bounding box with the first class.)
Therefore, claim 2 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 2 further recites additional elements of
The labeling includes outputting the set to receive selection of the first class specifying the first object image (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Therefore, claim 2 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 2 do not provide significantly more than the abstract idea itself, taken alone and in combination because
The labeling includes outputting the set to receive selection of the first class specifying the first object image is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
Therefore, claim 2 is subject-matter ineligible.
Regarding Claim 3:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 3 recites
Specifying the object image included in a space image based on the correlation (This limitation is a mental process as it encompasses a human mentally specifying the object image.)
Determining a class (This limitation is a mental process as it encompasses a human mentally determining a class.)
Therefore, claim 3 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 3 further recites additional elements of
Wherein the generating the secondarily learned model includes secondarily learning a weight of a model, for deriving a correlation between the second object image and the second class (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
By inputting the second space image to the primarily learned model (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Generating a model for determining a class (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Therefore, claim 3 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 3 do not provide significantly more than the abstract idea itself, taken alone and in combination because
Wherein the generating the secondarily learned model includes secondarily learning a weight of a model, for deriving a correlation between the second object image and the second class uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
By inputting the second space image to the primarily learned model is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
Generating a model for determining a class uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Therefore, claim 3 is subject-matter ineligible.
Regarding Claim 4:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 4 recites
Comparing a second class determined for the second object image with the first class (This limitation is a mental process as it encompasses a human mentally comparing classes.)
Maintaining a value of the second class when the second class and the first class are equal to each other (This limitation is a mental process as it encompasses a human mentally maintaining a value.)
Correcting the value of the second class to a value equal to the first class when the second class and the first class are different from each other (This limitation is a mental process as it encompasses a human mentally correcting the value of the second class.)
Therefore, claim 4 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 4 further recites additional elements of
Wherein the labeling of the second space image includes inputting the second space image to the primarily learned model (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
By the model (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Therefore, claim 4 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 4 do not provide significantly more than the abstract idea itself, taken alone and in combination because
Wherein the labeling of the second space image includes inputting the second space image to the primarily learned model is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
By the model uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Therefore, claim 4 is subject-matter ineligible.
Regarding Claim 5:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 5 recites
Wherein the bounding box is set to include one object image per one bounding box and to include an entire edge region of the object image in the bounding box (This limitation is a mental process as it encompasses a human mentally putting a bounding box in an image including an edge region.)
Therefore, claim 5 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 5 does not further recite any additional elements. Therefore, claim 5 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 5 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 5 is subject-matter ineligible.
Regarding Claim 6:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 6 recites
wherein the generating the second space image includes generating the second space image by changing an element value that is greater than a predetermined reference value to a greater element value and changing an element value smaller than the reference value to a smaller element value with respect to an element value (x, y, z) configuring RGB information of the pixel information included in the first space image (This limitation is a mental process as it encompasses a human mentally changing element values.)
Therefore, claim 6 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 6 does not further recite any additional elements. Therefore, claim 6 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 6 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 6 is subject-matter ineligible.
Regarding Claim 7:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 7 recites
wherein the generating the second space image includes generating the second space image from the first space image based on Equation 1 below: [Equation 1] dst(I)=round(max(0,min(α*src(I)- β, 255))) (src(I): element value (x, y, z) before pixel information is changed, α: constant, β: constant, and dst(I): element value (x',y',z') after pixel information is changed) (This limitation is a mathematical concept as it encompasses a mathematical equation.)
Therefore, claim 7 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 7 does not further recite any additional elements. Therefore, claim 7 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 7 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 7 is subject-matter ineligible.
Regarding Claim 8:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 8 recites
wherein the generating the second space image includes generating the second space image from the first space image based on Equation 2 below: [Equation 2] Y= 0.1667*R + 0.5*G + 0.3334*B (R: x of RGB information (x, y, z) of pixel information, G: y of GB information (x, y, z) of pixel information, B: z of GB information (x, y, z) of pixel information, and Y: element value (x', y',z') after pixel information is changed). (This limitation is a mathematical concept as it encompasses a mathematical equation.)
Therefore, claim 8 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 8 does not further recite any additional elements. Therefore, claim 8 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 8 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 8 is subject-matter ineligible.
Regarding Claim 9:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 9 recites
wherein the generating the second space image includes generating the second space image from the first space image based on Equations 3 and 4 below: [Equation 3] dst(I)=round(max(0,min(α*src(I)- β, 255))) (src(I): element value (x, y, z) before pixel information is changed, α: constant, β: constant, and dst(I): element value (x',y',z') after pixel information is changed) [Equation 4] Y= 0.1667*R + 0.5*G + 0.3334*B (R: x of RGB information (x, y, z) of pixel information, G: y of GB information (x, y, z) of pixel information, B: z of GB information (x, y, z) of pixel information, and Y: element value (x', y',z') after pixel information is changed). (This limitation is a mathematical concept as it encompasses a mathematical equation.)
Therefore, claim 9 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 9 does not further recite any additional elements. Therefore, claim 9 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 9 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 9 is subject-matter ineligible.
Regarding Claim 10:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 10 recites
wherein the generating the second space image includes generating the second space image by adding noise information to some of the pixel information included in the first space image (This limitation is a mental process as it encompasses a human mentally adding noise information to some of the pixel information.)
Therefore, claim 10 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 10 does not further recite any additional elements. Therefore, claim 10 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 10 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 10 is subject-matter ineligible.
Regarding Claim 11:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 11 recites
wherein the generating the second space image includes generating the second space image by adding noise information to pixel information of the first space image based on Equation 5 below: [Equation 5] dst(I)=round(max(0,min(src(I)
±
N, 255))) (src(I): element value (x, y, z) before pixel information is changed, N: random number, dst(I) : element value (x', y', z') after pixel information is changed) (This limitation is a mathematical concept as it encompasses a mathematical equation.)
Therefore, claim 11 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 11 does not further recite any additional elements. Therefore, claim 11 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 11 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 11 is subject-matter ineligible.
Regarding Claim 12:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 12 recites
wherein the generating the second space image includes generating the second space image by calculating a value (Rmax-RAVG, Gmax-GAVG, Bmax-BAVG) by subtracting an element average value (RAVG, GAVG, BAVG) of each of R, G, and B of a plurality of pixels from a maximum element value (Rmax, Gmax, Bmax) among element values of each of R, G, and B of the plurality of pixels included in a size of an NxN matrix (N being a natural number equal to or greater than 3) including a first pixel at a center among pixels included in the first space image and, when any one of element values of the (Rmax-RAVG, Gmax-GAVG, Bmax-BAVG) is smaller than a preset value, performing an operation of blurring the first pixel. (This limitation is a mathematical concept as it encompasses a mathematical equation.)
Therefore, claim 12 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 12 does not further recite any additional elements. Therefore, claim 12 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 12 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 12 is subject-matter ineligible.
Regarding Claim 13:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 13 recites
wherein the generating the second space image includes generating random number information based on standard Gaussian normal distribution with an average value of 0 and a standard deviation of 100 as much as a number of all pixels included in the first space image and generating the second space image into which noise is inserted by adding the random number information to each of the all pixels (This limitation is a mental process as it encompasses a human mentally generating a random number and adding it to each pixel.)
Therefore, claim 13 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 13 does not further recite any additional elements. Therefore, claim 13 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
Since there are no additional elements, claim 13 does not provide significantly more than the abstract idea itself, taken alone and in combination. Therefore, claim 13 is subject-matter ineligible.
Regarding Claim 14:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 14 recites
a correlation for determining a class of the object image included in the input space image (This limitation is a mental process as it encompasses a human mentally creating a correlating between a class and the object image.)
Therefore, claim 14 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 14 further recites additional elements of
wherein the generating the model includes setting a space image including an object image to an input layer of a neural network designed based on a faster region-based convolutional neural network (Faster R-CNN) algorithm, setting a bounding box including the object image and a class of the object image to an output layer (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
learning a weight of a neural network for deriving a correlation of a region of the bounding box of the object image included in the space image, input from the input space image (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Therefore, claim 14 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 14 do not provide significantly more than the abstract idea itself, taken alone and in combination because
wherein the generating the model includes setting a space image including an object image to an input layer of a neural network designed based on a faster region-based convolutional neural network (Faster R-CNN) algorithm, setting a bounding box including the object image and a class of the object image to an output layer is the well understood, routine, and conventional activity of “transmitting or receiving data over a network” (see MPEP 2106.05(d)(II); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network)).
learning a weight of a neural network for deriving a correlation of a region of the bounding box of the object image included in the space image, input from the input space image uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Therefore, claim 14 is subject-matter ineligible.
Regarding Claim 15:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 15 recites the same abstract ideas as claim 1. Therefore, claim 15 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 15 further recites additional elements of
An apparatus including a data augmentation-based object analysis model generated by the apparatus of claim 1 (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Therefore, claim 15 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 15 do not provide significantly more than the abstract idea itself, taken alone and in combination because
An apparatus including a data augmentation-based object analysis model generated by the apparatus of claim 1 uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Therefore, claim 15 is subject-matter ineligible.
Regarding Claim 16:
Subject Matter Eligibility Analysis Step 1:
Claim 16 recites a method and is thus a process, one of the four statutory categories of patentable subject matter.
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 16 recites
Generating a second space image by changing pixel information included in the first space image (This limitation is a mental process as it encompasses a human mentally creating a second image by changing pixel information.)
specifying a bounding box in a region including the first object image in the first space image (This limitation is a mental process as it encompasses a human mentally specifying a bounding box.)
labeling a first class specifying the first object image in the bounding box (This limitation is a mental process as it encompasses a human mentally labeling the first object.)
determining a class (This limitation is a mental process as it encompasses a human mentally determining a class.)
labeling the bounding box specifying a second object image in the second space image by the model and a second class determined with respect to the second object image by the model, to the second space image (This limitation is a mental process as it encompasses a human mentally label the bounding box.)
Therefore, claim 16 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 16 further recites additional elements of
a method performed by a data augmentation-based object analysis learning apparatus (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Acquiring a first space image including a first object image (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Primarily learning a weight of a model designed based on a predetermined object detection algorithm, for deriving a correlation between the first object image in the bounding box and the first class (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Inputting the first space image to the model (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Generating a model for determining a class (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Inputting the second space image to the primarily learned model (This element does not integrate the abstract idea into a practical application because it recites insignificant extra-solution activity of data gathering (see MPEP 2106.05(g)).)
Generating a model for secondarily learning the weight of the model based on the second space image (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)).)
Therefore, claim 16 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 16 do not provide significantly more than the abstract idea itself, taken alone and in combination because
A method performed by a data augmentation-based object analysis learning apparatus uses a computer as a tool to perform the abstract idea and cannot provide significantly more (see MPEP 2106.05(f)).
Acquiring a first space image including a first object image is the well understood, routine, and