REMARKS
`
`In an Office Action dated July 21, 2020, claims 1-24 were rejected. Herein, claims1, 7,
`
`12, 18, 23, and 24 have been amended. No new matter has been added. Additionally, claims 2
`
`and 13 have been cancelled without prejudice or disclaimer to the subject matter therein.
`
`Applicant respectfully requests further examination and reconsideration in view of the following
`
`remarks.
`
`I
`
`Claim Rejections under 35 U.S.C. 112
`
`Claims 7 and 18 were rejected under 35 U.S.C. 112(b) as being indefinite. Applicant
`
`notes that claims 7 and 8 have been amendedin view of the Examiner’s comments on pages 2-4
`
`of the Office Action. Accordingly, it is respectfully requested that the rejection of claims 7 and
`
`18 under 35 U.S.C. 112(b) be withdrawn.
`
`IL.
`
`Claim Rejections under 35 U.S.C. 102/103
`
`Claims 1, 3-12, and 14-24 wererejected under 35 U.S.C. 102(a)(2) as being anticipated
`
`by Terada (US 2018/0184123). Applicant notes that independent claims 1, 12, 23, and 24 have
`
`been amendedto incorporate the subject matter of cancelled claim 2, which along with claim 13,
`
`wasrejected under 35 U.S.C. 103 as being unpatentable over Terada in view of Rippel (US
`
`2018/0174052). Applicant respectfully submits that pending claims 1, 3-12, and 14-24 are
`
`patentable over any combination of Terada and Rippel in view ofthe following.
`
`Claim 1 recites the following features:
`
`generates a predicted image of an input imagethat is a current image to be encoded,
`
`based on generated data output from a generator network in response to a reference image being
`
`input to the generator network, the generator network being a neural network;
`
`feeds back, to the generator network, a probability that the predicted image matches the
`
`input image by inputting the input image andthe predicted imageto a discriminator network, the
`
`discriminator network being a neural network and constituting a generative adversarial network
`
`(GAN)with the generator network; and
`
`
`
`In an Office Action dated July 21, 2020, claims 1-24 were rejected. Herein, claims1, 7,
`
`12, 18, 23, and 24 have been amended. No new matter has been added. Additionally, claims 2
`
`and 13 have been cancelled without prejudice or disclaimer to the subject matter therein.
`
`Applicant respectfully requests further examination and reconsideration in view of the following
`
`remarks.
`
`I
`
`Claim Rejections under 35 U.S.C. 112
`
`Claims 7 and 18 were rejected under 35 U.S.C. 112(b) as being indefinite. Applicant
`
`notes that claims 7 and 8 have been amendedin view of the Examiner’s comments on pages 2-4
`
`of the Office Action. Accordingly, it is respectfully requested that the rejection of claims 7 and
`
`18 under 35 U.S.C. 112(b) be withdrawn.
`
`IL.
`
`Claim Rejections under 35 U.S.C. 102/103
`
`Claims 1, 3-12, and 14-24 wererejected under 35 U.S.C. 102(a)(2) as being anticipated
`
`by Terada (US 2018/0184123). Applicant notes that independent claims 1, 12, 23, and 24 have
`
`been amendedto incorporate the subject matter of cancelled claim 2, which along with claim 13,
`
`wasrejected under 35 U.S.C. 103 as being unpatentable over Terada in view of Rippel (US
`
`2018/0174052). Applicant respectfully submits that pending claims 1, 3-12, and 14-24 are
`
`patentable over any combination of Terada and Rippel in view ofthe following.
`
`Claim 1 recites the following features:
`
`generates a predicted image of an input imagethat is a current image to be encoded,
`
`based on generated data output from a generator network in response to a reference image being
`
`input to the generator network, the generator network being a neural network;
`
`feeds back, to the generator network, a probability that the predicted image matches the
`
`input image by inputting the input image andthe predicted imageto a discriminator network, the
`
`discriminator network being a neural network and constituting a generative adversarial network
`
`(GAN)with the generator network; and
`
`
`
`updates the generator network and the discriminator network to reduce difference
`
`between the input image and the predicted image and increase accuracy of discriminating
`
`between the input image and the predicted image.
`
`Applicant respectfully submits that the above-noted features of claim 1 are not disclosed,
`
`suggested, or otherwise rendered obvious by any combination of Terada and Rippel based on the
`
`following.
`
`On pages 13 and 14 of the Office Action, the Examiner appearsto rely on Rippel as
`
`teaching the features of claim 2.
`
`Rippel discloses technology of improving the accuracy achieved by an encoder and a
`
`discriminator by a GANfor image encoding technology. Although, FIG. 3 of Rippelillustrates
`
`that Prediction 318 is output from Discriminator 304, Applicant notes that Prediction 318
`
`indicates whether the input to Discriminator 304 is an original image or a reconstructed image
`
`(See [0006]). Accordingly, it is respectfully submitted that Prediction 318 is not a predicted
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`image.
`
`Therefore, Applicant notes that Discriminator 304 of Rippel discriminates whether the
`
`input is an original image or a reconstructed image, and as such,it is respectfully submitted that
`
`Rippel fails to teach that Discriminator 304 outputs a probability that a predicted image, which is
`
`neither an original image nor a reconstructed image, matches an original image to feed back the
`
`probability to the generator network.
`
`Applicant respectfully submits that any combination of Terada and Rippel would,at best,
`
`teach encoding an original image using the image encoding apparatus of Terada, generating a
`
`reconstructed image by further decoding the encodedoriginal image, and adjusting neural
`
`networks of predictors (i.e., the NN intra predictor and the NN inter predictor of Terada) of the
`
`image encoding apparatus, based onaresult of discriminating whetherthe inputto the
`
`discriminatoris an original image or a reconstructed image as taught by Rippel.
`
`10
`
`
`
`However, it is respectfully submitted that any combination of Terada and Rippelfails to
`
`teach that a predicted image is generated using a generator network, and that a probability that
`
`the predicted image matchesan original image(e.g., the input image required by claim 1) is fed
`
`back to the generator network using a discriminator network in order to update the generator
`
`network.
`
`Accordingly, any combination of Terada and Rippel necessarily fails to teach “feeds
`
`back, to the generator network, a probability that the predicted image matches the input image by
`
`inputting the input image andthe predicted imageto a discriminator network, the discriminator
`
`network being a neural network and constituting a generative adversarial network (GAN) with
`
`the generator network” and “updates the generator network and the discriminator network to
`
`reduce difference between the input image and the predicted image and increase accuracy of
`
`discriminating between the input image andthe predicted image,” as required by the above-noted
`
`features of claim 1.
`
`In view of the above, Applicant respectfully submits that any combination of Terada and
`
`Rippel fails to disclose, suggest, or otherwise render obvious the above-noted features of claim 1.
`
`Accordingly, claim 1 is patentable over any combination of Terada and Rippel.
`
`Claims 3-11 are patentable over any combination of Terada and Rippel basedat least on
`
`their dependency from claim 1.
`
`Claims 12, 23, and 24 recite features generally corresponding to the above-noted features
`
`of claim 1. Accordingly, Applicant respectfully submits that any combination of Terada and
`
`Rippel fails to disclose, suggest, or otherwise render obvious these corresponding features of
`
`claims 12, 23, and 24 for reasons similar to those discussed above with respect to claim 1, and as
`
`such, claims 12, 23, and 24 are patentable over any combination of Terada and Rippel.
`
`Claims 14-22 are patentable over any combination of Terada and Rippel based at least on
`
`their dependency from claim 12.
`
`11
`
`
`
`Il.
`
`Conclusion
`
`In view of the foregoing amendments and remarks, Applicant respectfully submits that
`
`claims 1, 3-12, and 14-24 are clearly in condition for allowance. An early notice thereof is
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`earnestly solicited.
`
`If, after reviewing this Amendment, the Examinerbelieves that there are any issues
`
`remaining which must be resolved before the application can be passedto issue, it is respectfully
`
`requested that the Examiner contact the undersigned by telephonein order to resolve such issues.
`
`Respectfully submitted,
`/Stephen W. Kopchik/
`2020.12.18 08:20:55 -05'00'
`
`Stephen W. Kopchik
`Registration No. 61,215
`Attorney for Applicant
`
`WENDEROTH, LIND & PONACK,L.L.P.
`1025 Connecticut Avenue, N.W., Suite 500
`Washington, D.C. 20036
`Telephone (202) 721-8200
`Facsimile (202) 721-8250
`December 18, 2020
`
`The Director is hereby authorized to charge any fees which may be required, or credit any overpayment
`to Deposit Account No. 23-0975.
`
`12
`
`
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