Prosecution Insights
Last updated: April 19, 2026
Application No. 18/976,662

DECODER, ENCODER, DECODING METHOD, AND ENCODING METHOD

Non-Final OA §102§103
Filed
Dec 11, 2024
Examiner
RIDER, JUSTIN W
Art Unit
2486
Tech Center
2400 — Computer Networks
Assignee
Panasonic Intellectual Property Corporation of America
OA Round
1 (Non-Final)
82%
Grant Probability
Favorable
1-2
OA Rounds
3y 10m
To Grant
90%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allow Rate
201 granted / 244 resolved
+24.4% vs TC avg
Moderate +8% lift
Without
With
+7.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 10m
Avg Prosecution
31 currently pending
Career history
275
Total Applications
across all art units

Statute-Specific Performance

§101
14.2%
-25.8% vs TC avg
§103
37.2%
-2.8% vs TC avg
§102
33.0%
-7.0% vs TC avg
§112
8.0%
-32.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 244 resolved cases

Office Action

§102 §103
DETAILED ACTION 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 . Information Disclosure Statement The information disclosure statements (IDSs) submitted on 12/11/2024 and 10/28/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner. Claim Rejections - 35 USC § 102 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. Claims 1-2, 4 and 19-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang et al., (WO 2022/072245 A1) referred to as WANG hereinafter. Regarding claim 1, WANG shows a decoder comprising: circuitry (Abstract); and memory coupled to the circuitry (Abstract), wherein in operation, the circuitry: decodes a plurality of sets of neural network information each of which identifies a neural network filter (Abstract describes syntax, indices as well as NN information for neural network model-based filters.); decodes, from one access unit, two or more sets of activation information each of which specifies one set of neural network information among the plurality of sets of neural network information (Paragraph [0084] discloses activation information in the form of indices for identifying select models for filtering.); and applies, to one picture, two or more neural network filters identified by two or more sets of neural network information specified by the two or more sets of activation information (Paragraph [0084] discloses where multiple filters can be applied to the target area.). Regarding claim 2, WANG shows the limitations of claim 1 as applied above, and further shows wherein the two or more sets of activation information each include a neural network identifier indicating a number for identifying one set of neural network information among the plurality of sets of neural network information (Paragraph [0084] as described above.), and the circuitry applies, to the one picture, the two or more neural network filters identified by two or more numbers indicated by two or more neural network identifiers included in the two or more sets of activation information (Paragraph [0084] as described above.). Regarding claim 4, WANG shows the limitations of claim 1 as applied above, and further shows wherein the circuitry sequentially applies the two or more neural network filters (Figure 5; Paragraph [0078] discloses four filter layers happening sequentially.) to the one picture in an order specified by the two or more sets of activation information (Figure 5; Paragraph [0081] discloses information that dictates the characteristics of the filters, which would include ordering.). Regarding claim 19, WANG shows an encoder comprising: Circuitry (Abstract); and memory coupled to the circuitry (Abstract), wherein in operation, the circuitry: encodes a plurality of sets of neural network information each of which identifies a neural network filter (FIG. 6 and Paragraphs [0104]-[0135] generally disclose the encoding process; Paragraph [0127] discloses an index for identifying the above.); and encodes, into one access unit, two or more sets of activation information each of which specifies one set of neural network information among the plurality of sets of neural network information, and the two or more sets of activation information are used to apply, to one picture, two or more neural network filters identified by two or more sets of neural network information specified by the two or more sets of activation information (Paragraph [0125] discloses the encoding of NN information related to filtering that is used for decoding.). Regarding claim 20, WANG shows a decoding method comprising: decoding a plurality of sets of neural network information each of which identifies a neural network filter (Abstract describes syntax, indices as well as NN information for neural network model-based filters.); decoding, from one access unit, two or more sets of activation information each of which specifies one set of neural network information among the plurality of sets of neural network information (Paragraph [0084] discloses activation information in the form of indices for identifying select models for filtering.); and applying, to one picture, two or more neural network filters identified by two or more sets of neural network information specified by the two or more sets of activation information (Paragraph [0084] discloses where multiple filters can be applied to the target area.). Regarding claim 21, WANG shows an encoding method comprising: encoding a plurality of sets of neural network information each of which identifies a neural network filter (FIG. 6 and Paragraphs [0104]-[0135] generally disclose the encoding process; Paragraph [0127] discloses an index for identifying the above.); and encoding, into one access unit, two or more sets of activation information each of which specifies one set of neural network information among the plurality of sets of neural network information, wherein the two or more sets of activation information are used to apply, to one picture, two or more neural network filters identified by two or more sets of neural network information specified by the two or more sets of activation information (FIG. 6 and Paragraphs [0104]-[0135] generally disclose the encoding process; Paragraph [0125] discloses the encoding of NN information related to filtering that is used for decoding.). Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claim(s) 3 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over WANG in view of Deshpande (US 2022/0321919 A1) referred to as DESHPANDE hereinafter. Regarding claim 3, WANG shows the limitations of claim 1 as applied above, however failing to but DESHPANDE does further show wherein the two or more sets of activation information each include an image identifier specifying the one picture, and the circuitry applies the two or more neural network filters to the one picture specified by the image identifier (While WANG Paragraph [0084] discloses identification for a specific target area for a one picture is isn’t explicitly a picture and a count; DESHPANDE: Paragraph [0133], top of page 19 discloses using an actual picture order count to identify pictures to be decoded.). Both WANG and DESHPANDE are analogous art in that they are in the same field of endeavor. Therefore, it would have been obvious to one possessing ordinary skill in the art before the effective time of invention to modify WANG in the spirit of DESHPANDE because as described in the Background (Paragraph [0003] of DESHPANDE), these were mere ideas contemplated to improve the ever-growing complexity of video compression, whereas DESHPANDE actually implemented them to fully unleash the power of Neural Network based filtering.). Regarding claim 8, WANG shows the limitations of claim 3 as applied above, however failing to but DESHPANDE does further show wherein the image identifier is a value of picture order count (POC) of the one picture (Paragraph [0133], top of page 19 discloses using an actual picture order count to identify pictures to be decoded.). Both WANG and DESHPANDE are analogous art in that they are in the same field of endeavor. Therefore, it would have been obvious to one possessing ordinary skill in the art before the effective time of invention to modify WANG in the spirit of DESHPANDE because as described in the Background (Paragraph [0003] of DESHPANDE), these were mere ideas contemplated to improve the ever-growing complexity of video compression, whereas DESHPANDE actually implemented them to fully unleash the power of Neural Network based filtering.). Allowable Subject Matter Claims 5-7 and 9-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUSTIN W. RIDER whose telephone number is (571)270-1068. The examiner can normally be reached Monday-Friday, 7.00 am - 4.30 pm. 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, Jamie J Atala can be reached at (571) 272-7384. 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. JUSTIN W. RIDER Primary Patent Examiner Art Unit 2486 /Justin W Rider/Primary Patent Examiner, Art Unit 2486
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Prosecution Timeline

Dec 11, 2024
Application Filed
Dec 18, 2025
Non-Final Rejection — §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
82%
Grant Probability
90%
With Interview (+7.7%)
3y 10m
Median Time to Grant
Low
PTA Risk
Based on 244 resolved cases by this examiner. Grant probability derived from career allow rate.

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