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 .
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.
DETAILED ACTION
This communication is in response to Application No. 18/673,200 filed on May 23, 2024 and amendment presented on December 23, 2025 which amends claims 1, 7-8 and 14-15, canceled claims 4, 11 and 18 and presents arguments, is hereby acknowledged. Claims 1-3, 5-10, 12-17 and 19-20 are currently pending and subject to examination.
Response to Arguments
On pages 8-10 of the response filed December 23, 2025, Applicant addresses the 35 U.S.C. 112 and 35 U.S.C. § 103 rejection made on the September 26, 2025 Non-Final Rejection. Applicant's arguments, regarding the rejections under 35 U.S.C. 112 and 35 U.S.C. § 103, have been fully considered.
Rejections under 35 U.S.C. § 112
5. Applicant’s claim amendment and arguments, filed in the response dated December 23, 2025 regarding the rejections of claims 7 and 14 under § 112(b) have been fully considered and are persuasive. All outstanding rejections of claims 7 and 14 under § 112(b) are hereby withdrawn.
Rejections under 35 U.S.C. § 103
6. Applicants argue at page 9 of the remarks, as filed that the combination of He and Zhang does not disclose “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first type information indicating a type of the first video frame data packet” as recited by amended independent claim 1.
The examiner respectfully disagrees and finds these arguments unpersuasive. The courts have explicitly stated that the prior art need not be solving the same problem as the applicant. SeeKSR Int'l Co. v. Teleflex, Inc., 550 U.S. 398 (2007). For example, one may arrive at identical claimed invention by solving a completely different problem.
In addition, the Applicant’s specification does not provide an explicit definition of “first type information indicating a type of the first video frame data packet”. According to MPEP 2111, examiner obliged to give the terms or phrases their broadest reasonable interpretation definition, consistent with the specification, and awarded by one of an ordinary skill in the art unless applicant has provided some indication of the definition of the claimed terms or phrases. Applicant’s specification states, in paragraph 0022, 0050, discloses For example, the first type information may be represented by a number. For example, the first type information in the first video frame data packet may be represented by a number 1, to indicate that a type of a data packet whose type information is 1 is a video frame data packet. specification states, in paragraph 0051 discloses For example, the first type information may be represented by a letter. For example, the first type information in the first video frame data packet may be represented by a letter A, to indicate that a type of a data packet whose type information is A is a video frame data packet.
Specifically, the examiner cited prior art reference “He” teaches “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first type information indicating a type of the first video frame data packet” as recited by amended independent claim 1.
He describes obtaining a first video frame data (e.g. first video frame data packet) and a reconstructed image as input to neural network corresponding to original video data (e.g. a first neural network data packet) which includes neural network information comprises network parameter (e.g. neural network parameter information) and video frame data (e.g. first video frame data packet) includes identification information such as group of video frame data, number, name and so on in the corresponding first video frame data (e.g. first video frame data packet) (e.g. first identification information and first type information) (He: [paragraph 0035, 0052-0055, 0060]).Thus, the combination of He and Zhang still disclose “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first type information indicating a type of the first video frame data packet” as recited by amended independent claim 1.
Applicants further argue at page 9 of the remarks, as filed that the combination of He and Zhang does not disclose “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first identification information and first type information indicating a type of the first video frame data packet” as recited by amended independent claim 1.
The examiner respectfully disagrees and finds these arguments unpersuasive. The courts have explicitly stated that the prior art need not be solving the same problem as the applicant. SeeKSR Int'l Co. v. Teleflex, Inc., 550 U.S. 398 (2007). For example, one may arrive at identical claimed invention by solving a completely different problem.
Specifically, the examiner cited prior art reference “He” teaches “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first identification information and first type information indicating a type” as recited by amended independent claim 1.
He describes obtaining a first video frame data (e.g. first video frame data packet) and a reconstructed image as input to neural network corresponding to original video data (e.g. a first neural network data packet) which includes neural network information comprises network parameter (e.g. neural network parameter information) and video frame data (e.g. first video frame data packet) includes identification information such as group of video frame data, number, name and so on in the corresponding first video frame data (e.g. first video frame data packet) (e.g. first identification information and first type information) and group of video frame data, number, name and so on in the corresponding first video frame data (e.g. first video frame data packet) (e.g. first identification information and first type information) indicating n original video frames; n is a real number greater than zero. For example, 1 original video frame and the corresponding reconstructed image and the type of video information may include at least one of the following: video content, video scene information, video caption information (e.g. first type information indicating a type) (He: [paragraph 0035, 0052-0055, 0060-0062]).Thus, the combination of He and Zhang still disclose “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first identification information and first type information indicating a type” as recited by amended independent claim 1.
Applicants further argue at page 9 of the remarks, as filed that the combination of He and Zhang does not disclose “sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the first type information” as recited by amended independent claim 1.
The examiner respectfully disagrees and finds these arguments unpersuasive. The courts have explicitly stated that the prior art need not be solving the same problem as the applicant. SeeKSR Int'l Co. v. Teleflex, Inc., 550 U.S. 398 (2007). For example, one may arrive at identical claimed invention by solving a completely different problem.
Specifically, the examiner cited prior art reference “Zhang” teaches “sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the first type information” as recited by amended independent claim 1.
Zhang describes sending video frame data packet and neural network data based on video frame data packet identification information (e.g. first identification information) and neural network data identification information (e.g. second identification information) and video frame data packet and neural network data includes a packet identifier (PID) is used to identify type of video frame data packet and neural network data representation (e.g. and the first type information) (Zhang: [paragraph 0020-0021, 0034, 0039-0042, 0063-0064). Thus, the combination of He and Zhang still disclose “sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the first type information” as recited by amended independent claim 1.
Therefore, the combination of He and Zhang still disclose “receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first type information indicating a type of the first video frame data packet” ,
“receiving a first video frame data packet and a first neural network data packet, the first video frame data packet comprises first identification information and first type information indicating a type of the first video frame data packet” and “sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the first type information” as recited by amended independent claim 1.Therefore, Applicant’s arguments are unpersuasive. Therefore, the rejection of claim 1 is hereby maintained.
Applicants argue claims 8 and 15 based on the arguments presented for Claim 1 at page 10 of the remarks. The same explanation is applicable to claims 8 and 15 as mentioned above with respect to claim 1.
Dependent claims 2-3, 5-7, 9-10, 12-14, 16-17 and 19-20
Applicant’s argues these claims conditionally based upon arguments presented for their parent claim(s). Applicant’s arguments are unpersuasive and therefore, the rejections of these claims 2-3, 5-7, 9-10, 12-14, 16-17 and 19-20 are hereby maintained.
Claim Rejections - 35 USC § 103
7. 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.
8. 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.
9. Claims 1-3, 5, 8-10, 12 and 15-17, 19 are rejected under 35 U.S.C. 103 as being unpatentable over HE et al. (CN 112188202 A, hereinafter as “HE”); in view of ZHANG et al. (US 20230217028 A1, hereinafter as “ZHANG”).
Regarding Claim 1, HE teaches a data transmission method, comprising: receiving a first video frame data packet and a first neural network data packet,
the first neural network data packet carrying neural network parameter information ([paragraph 0009-0010, 0035, 0052-0055] describes obtaining a first video frame data (e.g. first video frame data packet) and a reconstructed image as input to neural network corresponding to original video data (e.g. a first neural network data packet) which includes neural network information comprises network parameter (e.g. neural network parameter information)),
the neural network parameter information is used for processing data of the first video frame data packet, the first video frame data packet comprises first identification information and first type information indicating a type of the first video frame data packet, the first neural network data packet comprises second identification information ([paragraph 0035, 0052-0055] describes neural network parameter information for constructing repair neural network, restoring the reconstructed image obtained by decoding the first video frame data to obtain the repair video of the target video (e.g. neural network parameter information is used for processing data of the first video frame data packet) and the first video frame data (e.g. first video frame data packet) includes identification information such as group of video frame data (e.g. first identification information), reconstructed image as input to neural network corresponding to original video data (e.g. a first neural network data packet) includes another identifications information such as group of reconstructed images as input to neural network corresponding to original video data (e.g. second identification information) [paragraph 0035, 0052-0055, 0060-0062] describes neural network information comprises network parameter (e.g. neural network parameter information) and video frame data (e.g. first video frame data packet) includes identification information such as group of video frame data, number, name and so on in the corresponding first video frame data (e.g. first video frame data packet) (e.g. first identification information and first type information) and group of video frame data, number, name and so on in the corresponding first video frame data (e.g. first video frame data packet) (e.g. first identification information and first type information) indicating n original video frames; n is a real number greater than zero. For example, 1 original video frame and the corresponding reconstructed image and the type of video information may include at least one of the following: video content, video scene information, video caption information (e.g. first type information indicating a type)),
and the first identification information and the second identification information each indicate a correspondence between the first video frame data packet and the first neural network data packet ([paragraph 0035, 0052-0055] describes the first video frame data (e.g. first video frame data packet) includes identification information such as group of video frame data (e.g. first identification information) and reconstructed image as input to neural network corresponding to original video data (e.g. a first neural network data packet) includes another identifications information such as group of reconstructed images as input to neural network corresponding to original video data (e.g. second identification information) which determine it corresponds to the same target video according to the first video frame data (e.g. first video frame data packet) and the reconstructed image as input to neural network corresponding to original video data (e.g. the first neural network data packet));
HE fails to teach and sending the first video frame data packet and the first neural network data packet based on the first identification information and the second identification information, and the first type information.
However, ZHANG teaches sending the first video frame data packet and the first neural network data packet based on the first identification information and the second identification information, and the first type information ([paragraph 0020-0021, 0034, 0039-0042, 0063-0064] describes sending video frame data packet and neural network data based on video frame data packet identification information (e.g. first identification information) and neural network data identification information (e.g. second identification information) and video frame data packet and neural network data includes a packet identifier (PID) number is used to identify type of video frame data packet and neural network data representation (e.g. and the first type information)).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the teachings of HE to include sending the first video frame data packet and the first neural network data packet based on the first identification information and the second identification information and the first type information as taught by ZHANG. One ordinary skill in the art would be motivated to utilize the teachings of HE in the ZHANG system in order to utilize neural networks in an ever-increasing number of applications for many different types of devices ([paragraph 0061] in ZHANG).
Regarding Claim 2, the combination of HE and ZHANG teaches the method, wherein the first identification information indicates a group of the first video frame data packet (HE: [paragraph 0035, 0052-0055] describes the first video frame data (e.g. first video frame data packet) includes identification information such as group of video frame data (e.g. first identification information).
Regarding Claim 3, the combination of HE and ZHANG teaches the method, wherein the second identification information indicates a group of the first neural network data packet (HE: [paragraph 0035, 0052-0055] describes reconstructed image as input to neural network corresponding to original video data (e.g. a first neural network data packet) includes another identifications information such as group of reconstructed images as input to neural network corresponding to original video data (e.g. second identification information)).
Regarding Claim 5, the combination of HE and ZHANG teaches the method, wherein the first neural network data packet further comprises second type information, and the second type information indicates a type of the first neural network data packet; and the sending the first video frame data packet and the first neural network data packet based on the first identification information and the second identification information sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the first type information (CHANG: [paragraph 0020, 0034, 0039-0042, 0063-0034] describes neural network data comprises another type information (e.g. second type information) which indicates type of neural network data and sending video frame data packet and neural network data based on video frame data packet identification information (e.g. first identification information) and neural network data identification information (e.g. second identification information) comprises:
sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the second type information (CHANG: [paragraph 0020, 0034, 0039-0042, 0063-0034] describes sending video frame data packet and neural network data based on video frame data packet identification information (e.g. first identification information) and neural network data identification information (e.g. second identification information) and another type information (e.g. second type information) which indicates type of neural network data).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the teachings of HE to include wherein the first neural network data packet further comprises second type information, indicates a type of the first neural network data packet and sending the first video frame data packet and the first neural network data packet based on the first identification information, the second identification information, and the second type information as taught by ZHANG. One ordinary skill in the art would be motivated to utilize the teachings of HE in the ZHANG system in order to utilize neural networks in an ever-increasing number of applications for many different types of devices ([paragraph 0061] in ZHANG).
Regarding claims 8-10, these claims contain limitations found within that of claims 1-3 and the same rationale to rejections are used.
Regarding claim 12, this claim contains limitations found within that of claim 5 and the same rationale to rejection is used.
Regarding claims 15-17, these claims contain limitations found within that of claims 1-3 and the same rationale to rejections are used.
Regarding claim 19, this claim contains limitations found within that of claim 5 and the same rationale to rejection is used.
10. Claims 6-7, 13-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over HE et al. (CN 112188202 A, hereinafter as “HE”); in view of ZHANG et al. (US 20230217028 A1, hereinafter as “ZHANG”); and further in view of KIM et al. (US 2022/0295337 A1, hereinafter as “KIM’).
Regarding Claim 6, HE and ZHNAG fails to teach the method, wherein the first video frame data packet is carried on a first quality of service (QoS) flow; and the first neural network data packet is carried on a second QoS flow.
However, KIM teaches the method, wherein the first video frame data packet is carried on a first quality of service (QoS) flow; and the first neural network data packet is carried on a second QoS flow ([paragraph 0072-0073, 0155, 0177, 0239] describes video data packet is carried on a PC5 QoS flow and neural network data is carried on another PC5 QoS flow (e.g. second QoS flow)).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the teachings of HE/CHANG to include wherein the first video frame data packet is carried on a first quality of service (QoS) flow; and the first neural network data packet is carried on a second QoS flow as taught by KIM. One ordinary skill in the art would be motivated to utilize the teachings of HE/ZHANG in the KIM system in order to derive plurality of QoS (Quality of Service) parameters for a plurality of services ([paragraph 0018] in KIM).
Regarding Claim 7, the combination of HE and ZHNAG teaches the method, wherein the sending the first video frame data packet and the first neural network data packet based on the first identification information and the second identification information comprises (ZHANG: [paragraph 0020, 0034, 0039-0042, 0063-0034] describes sending video frame data packet and neural network data based on video frame data packet identification information (e.g. first identification information) and neural network data identification information (e.g. second identification information)):
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the teachings of HE to include sending the first video frame data packet and the first neural network data packet based on the first identification information and the second identification information as taught by ZHANG. One ordinary skill in the art would be motivated to utilize the teachings of HE in the ZHANG system in order to utilize neural networks in an ever-increasing number of applications for many different types of devices ([paragraph 0061] in ZHANG).
HE and ZHANG fails to teach mapping, to a radio resource based on the first identification information and the second identification information, the data packets carried on the first QoS flow and the second QoS flow; and transmitting the data packets.
However, KIM teaches mapping, to a radio resource based on the first identification information and the second identification information, the data packets carried on the first QoS flow and the second QoS flow; and transmitting the data packets ([paragraph 0095-0096, 0123, 0164-0165, 0177] describes mapping radio resources based on group identifier information and another group identifier information (e.g. the first identification information and the second identification information) and data packets carried on PC5 QoS flow and another PC5 QoS flow (e.g. second QoS flow) and transmitting data packets).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filling date of the claimed invention to modify the teachings of HE/CHANG to include mapping, to a radio resource based on the first identification information and the second identification information, the data packets carried on the first QoS flow and the second QoS flow and transmitting the data packets as taught by KIM. One ordinary skill in the art would be motivated to utilize the teachings of HE/ZHANG in the KIM system in order to derive plurality of QoS (Quality of Service) parameters for a plurality of services ([paragraph 0018] in KIM).
Regarding claims 13-14, these claims contain limitations found within that of claims 6-7 and the same rationale to rejections are used.
Regarding claim 20, this claim contains limitations found within that of claim 6 and the same rationale to rejection is used.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
- Mukherjee et al., US 2020/0184603 A1, The described technology is generally directed towards guided restoration is used to restore video data degraded from a video frame.
- Aksu et al., US 12219204 B2, A method is provided for defining a metadata box of a neural network representation (NNR) item data.
THIS ACTION IS MADE FINAL. 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.
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/M.J.S/Examiner, Art Unit 2459 /SCHQUITA D GOODWIN/Primary Examiner, Art Unit 2459