Prosecution Insights
Last updated: April 19, 2026
Application No. 18/799,408

PROGRESSIVE CODING FOR AUTOENCODERS

Final Rejection §103
Filed
Aug 09, 2024
Examiner
TORRENTE, RICHARD T
Art Unit
2485
Tech Center
2400 — Computer Networks
Assignee
Synaptics Incorporated
OA Round
2 (Final)
69%
Grant Probability
Favorable
3-4
OA Rounds
3y 3m
To Grant
83%
With Interview

Examiner Intelligence

Grants 69% — above average
69%
Career Allow Rate
717 granted / 1039 resolved
+11.0% vs TC avg
Moderate +14% lift
Without
With
+14.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
40 currently pending
Career history
1079
Total Applications
across all art units

Statute-Specific Performance

§101
6.5%
-33.5% vs TC avg
§103
51.9%
+11.9% vs TC avg
§102
25.9%
-14.1% vs TC avg
§112
8.3%
-31.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1039 resolved cases

Office Action

§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 . Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, 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. Claims 1-2, 4-13 and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nguyen et al. (US 2025/0254366) in view of Han et al. (US 2023/0336742). Regarding claim 1, Nguyen discloses a method for encoding images (see 100 in fig. 1), comprising: encoding an image (see 160 in fig. 1) as a tensor of latent attributes (see 162 in fig. 1; e.g. see ¶ [0181]) having a plurality of first channels (see 412-428 in fig. 4) based on one or more first layers of a neural network model (see 412-428 in fig. 4; e.g. see ¶ [0101]); recombining the plurality of first channels (see 460-464 in fig. 4), as a plurality of second channels (see 471-477 in fig. 4) having a prioritized order (see P2-P5 in fig. 4), based on one or more second layers (see 450-454 in fig. 4) of the neural network model. Although Nguyen discloses progressively transmitting the plurality of second channels over a communication channel (see 122 in fig. 1), wherein the one or more second layers trained to assign a priority to each channel of the plurality of second channels (see P2-P5 in fig. 4), it is noted that Nguyen does not provide the particular wherein the channels transmission is based on a prioritized order, and wherein the assign a priority to each channel of the plurality of second channels are based on a contribution of the channel to a quality level of the image. However, Han discloses a scalable video coding wherein the channels transmission is based on a prioritized order (e.g. see ¶ [0008], [0067]), and wherein the assign a priority to each channel of the plurality of second channels (e.g. see ¶ [0008], [0067]) are based on a contribution of the channel to a quality level of the image (e.g. see quality of resolution of base and enhancement layer ¶ [0042], [0046]). Given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate Han teachings of channel priority transmission into Nguyen channel transmission for the benefit of reducing image tearing and freezing and image quality deterioration occurring in wireless projection, and improve user experience. Regarding claims 2 and 13, Nguyen further discloses wherein the one or more first layers of the neural network model are trained to perform an encoding operation associated with an autoencoder (see 160 in fig. 1). Regarding claims 4 and 15, the references further discloses wherein the progressive transmission of the plurality of second channels comprises: transmitting each channel of the plurality of second channels, in order of the assigned priorities (e.g. see Han ¶ [0008], [0067]), so that the channel assigned the highest priority is transmitted before the channel assigned the lowest priority (e.g. see Han ¶ [0067]). Regarding claims 5-6 and 16-17, the references do not disclose wherein the progressive transmission of the plurality of second channels further comprises: terminating the transmission of the plurality of second channels prior to transmitting one or more channels of the plurality of second channels over the communication channel, wherein the transmission is terminated based at least in part on a bandwidth of the communication channel. Although it is not explicitly recited, it is conventional in the art for terminating transmission of a channel based on bandwidth restriction. The Examiner takes official notice that termination transmission is well known in the art. Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate terminating transmission of channels for the benefit of preventing data loss or delay due to bandwidth restriction. Regarding claims 7 and 18, Nguyen further discloses wherein the progressive transmission of the plurality of second channels comprises: generating a hyperlatent based on a subset of channels of the plurality of second channels (see P2-P5 in fig. 4); determining an entropy model based on the hyperlatent (see 738 in fig. 7); and encoding each channel in the subset of channels based on the entropy model prior to transmitting the channel over the communication channel (see 738 in fig. 7). Regarding claim 8, Nguyen further discloses wherein the hyperlatent is a latent representation of the entropy model (see 738 in fig. 7). Regarding claims 9 and 19, Nguyen does not discloses comprising: discarding one or more channels of the entropy model prior to encoding the subset of channels. Although it is not explicitly recited, it is conventional in the art for discarding a channel of prior to encoding the subset of channels. The Examiner takes official notice that discarding a channel of prior to encoding the subset of channels is well known in the art. Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was made to incorporate terminating transmission of channels for the benefit of reducing processing time and preventing data loss or delay due to bandwidth restriction. Regarding claims 10 and 20, the references further disclose wherein the subset of channels excludes one or more channels, of the plurality of second channels, that are not transmitted over the communication channel (e.g. see Han ¶ [0008], [0067]). Regarding claim 11, Nguyen further discloses comprising: transmitting the hyperlatent over the communication channel (see 122 in fig. 1). Regarding claim 12, the claim(s) recite an encoder comprising: a processing system; and a memory storing instructions that, when executed by the processing system (see fig. 2A) with analogous limitations to claim 1, and is/are therefore rejected on the same premise. Response to Arguments Applicant's arguments filed 1/28/26 have been fully considered but they are not persuasive. Applicant argued that the one or more second layers of the neural network model are trained to assign a priority to each channel of the plurality of second channels based on a contribution of the channel to a quality level of the image. The Examiner respectfully disagrees (see mapping above). Incorporating the teaching of Han into Nguyen would result in the one or more second layers of the neural network model are trained to assign a priority to each channel of the plurality of second channels based on a contribution of the channel to a quality level of the image (see Nguyen 412-424 in fig. 4 resulting in transmitting P2-P5 in priority based on Han transmitting priority of base first then first enhancement layers, then second enhancement layer, then etc.) Citation of Pertinent Art The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. 1. Lee et al. (US 2018/0269969), discloses layered coding priorities and termination of transmission. 2. Di et al. (US 2024/0205432), discloses scalable coding priorities and discarding of transmission. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICHARD T TORRENTE whose telephone number is (571)270-3702. The examiner can normally be reached M-F: 6:45-3:15 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, Jay Patel can be reached at (571) 272-2988. 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. /RICHARD T TORRENTE/Primary Examiner, Art Unit 2485
Read full office action

Prosecution Timeline

Aug 09, 2024
Application Filed
Oct 16, 2025
Examiner Interview (Telephonic)
Nov 12, 2025
Non-Final Rejection — §103
Jan 28, 2026
Response Filed
Mar 13, 2026
Final Rejection — §103 (current)

Precedent Cases

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

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Prosecution Projections

3-4
Expected OA Rounds
69%
Grant Probability
83%
With Interview (+14.0%)
3y 3m
Median Time to Grant
Moderate
PTA Risk
Based on 1039 resolved cases by this examiner. Grant probability derived from career allow rate.

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