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 .
Response to Arguments
Applicant's arguments filed 2/3/26 have been fully read and considered but they are not persuasive.
Claims 1-13 and 15-23 are allowed due to amendments to independent claims 1 and 19-23 with incorporation of patentable subject matter that was objected to in the previous Office Action mailed 10/7/25. Peruse the reasons as provided below in the allowable subject matter section of this current Office Action.
However, newly added independent claim 24 is not patentable under Kadono (US 2004/0076237) because bitstream claims are not considered to be patentable subject matter. Thus, claim 24 is rejected under 35 USC 102(a)(1) in view of Kadono (US 2004/0076237). Peruse the rejection below for elaboration.
With regards to foreign priority issues, a certified copy of European Application Number EP22168623.1 has been received on 2/17/26. Thus, the objection to foreign priority issues has been withdrawn.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/27/25 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Claim Rejections - 35 USC § 102
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.
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.
Claim 24 is rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kadono (US 2004/0076237).
Regarding claim 24, Kadono discloses a non-transitory digital storage medium having a bitstream stored thereon (paragraph [257], Kadono discloses a computer readable data medium such as CD-ROM, floppy disk, hard disk drive, etc.); wherein the bitstream comprises an encoded representation of a plurality of neural network parameter values of a first multi-dimensional array of neural network parameters; wherein the bitstream comprises an encoded representation of a list of skipped rows for a decoder-sided decoding, the decoder sided decoding comprising acquiring the first multi-dimensional array comprising the plurality of neural network parameter values using a decoding of neural network parameters; entering decoded neural network coefficients into the first multidimensional array at respective positions described by respective sets of array indices; and acquiring a re-ordered multidimensional array using a reordering, in which a first dimension of the first multi-dimensional array is rearranged to a different dimension in the re-ordered multidimensional array; wherein the list of skipped rows enables deciding, for the decoder sided decoding, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the first multidimensional array, whether to use a default value for a given neural network parameter or whether to determine the given neural network parameter using a decoding (paragraph [257], Kadono discloses a computer readable data medium such as CD-ROM, floppy disk, hard disk drive, etc.).
Note claim 24 is directed to “a non-transitory digital storage medium’'. The non-transitory digital storage medium without functional relationship between the digital storage medium and the rest of recited features of the claim “…having a bitstream stored thereon; wherein the bitstream comprises an encoded representation of a plurality of neural network parameter values of a first multi-dimensional array of neural network parameters; wherein the bitstream comprises an encoded representation of a list of skipped rows for a decoder-sided decoding, the decoder sided decoding comprising acquiring the first multi-dimensional array comprising the plurality of neural network parameter values using a decoding of neural network parameters; entering decoded neural network coefficients into the first multidimensional array at respective positions described by respective sets of array indices; and acquiring a re-ordered multidimensional array using a reordering, in which a first dimension of the first multi-dimensional array is rearranged to a different dimension in the re-ordered multidimensional array; wherein the list of skipped rows enables deciding, for the decoder sided decoding, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the first multidimensional array, whether to use a default value for a given neural network parameter or whether to determine the given neural network parameter using a decoding”. When determining the scope of the claim, the above features of claim 24 were not given patentable weight. See MPEP 2111.05 (III). Thus, the computer-readable data recording medium such as CD-ROM, floppy disk, or a hard disk drive disclosed in Kadono meets Applicant’s claim 24.
Allowable Subject Matter
Claims 1-13 and 15-23 are allowed.
The following is a statement of reasons for the indication of allowable subject matter: the present invention pertains to compression and decompression of video data with a neural network.
With regards to claim 1, Wang (WO 2020/190772) discloses a decoder for providing decoded parameters of a neural network (paragraph 174) on the basis of an encoded representation (paragraph 47),
wherein the decoder is configured to acquire a first multi-dimensional array (paragraph 47) comprising a plurality of neural network parameter values using a decoding of neural network parameters (paragraph 80);
wherein the decoder is configured to acquire a re-ordered multidimensional array using a reordering (paragraph 47).
Kang (US 2023/0269399) discloses a decoder for providing decoded parameters of a neural network on the basis of an encoded representation (paragraph 74), in which a first dimension of the first multi-dimensional array is rearranged to a different dimension in the re-ordered multidimensional array (paragraph 84).
The prior art, either singularly or in combination, does not disclose the limitation “…wherein the decoder is configured to decode a list of skipped rows; wherein the decoder is configured to enter decoded neural network coefficients into the first multidimensional array at respective positions described by respective sets of array indices; wherein the decoder is configured decide, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the first multidimensional array, whether to use a default value for a given neural network parameter or whether to determine the given neural network parameter using a decoding” of claim 1.
Note that prior arts were found and applied above for claim 1. However, in view of further consideration of the prior art teachings, it is determined that there is no strong motivation or reasoning to combine the references to arrive at the claimed invention of claim 1.
Thus, the prior art does not disclose the aforementioned limitation of claim 1.
With regards to claim 19, Wang (WO 2020/190772) discloses an encoder (paragraph 169) for providing an encoded representation of parameters of a neural network (paragraph 47),
wherein the encoder is configured to acquire a re-ordered multidimensional array using a reordering (paragraph 47);
wherein the encoder is configured to encode the reordered multi-dimensional array (paragraph 47).
Kang (US 2023/0269399) discloses an encoder for providing an encoded representation of parameters of a neural network (paragraph 28), in which a given dimension of a given multi-dimensional array of neural network parameters is rearranged to a first dimension in the re-ordered multidimensional array (paragraph 66).
The prior art, either singularly or in combination, does not disclose the limitation “wherein the encoder is configured to encode a list of skipped rows; wherein the encoder is configured to encode neural network coefficients of the reordered multidimensional array at respective positions described by respective sets of array indices; wherein the encoder is configured decide, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the reordered multidimensional array, whether to encode or not a neural network parameter at a current position” of claim 19.
Note that prior arts were found and applied above for claim 19. However, in view of further consideration of the prior art teachings, it is determined that there is no strong motivation or reasoning to combine the references to arrive at the claimed invention of claim 19.
Thus, the prior art does not disclose the aforementioned limitation of claim 19.
With regards to claim 20, Wang (WO 2020/190772) discloses a method for providing decoded parameters of a neural network (paragraph 174) on the basis of an encoded representation (paragraph 47), wherein the method comprises:
acquiring a first multi-dimensional array (paragraph 47) comprising a plurality of neural network parameter values using a decoding of neural network parameters (paragraph 80);
wherein the method comprises acquiring a re-ordered multidimensional array using a reordering (paragraph 47).
Kang (US 2023/0269399) discloses a method for providing decoded parameters of a neural network on the basis of an encoded representation (paragraph 74), wherein the method comprises: in which a first dimension of the first multi-dimensional array is rearranged to a different dimension in the re-ordered multidimensional array (paragraph 84).
The prior art, either singularly or in combination, does not disclose the limitation “…wherein the method comprises decoding a list of skipped rows; wherein the method comprises entering decoded neural network coefficients into the first multidimensional array at respective positions described by respective sets of array indices; wherein the method comprises deciding, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the first multidimensional array, whether to use a default value for a given neural network parameter or whether to determine the given neural network parameter using a decoding” of claim 20.
Note that prior arts were found and applied above for claim 20. However, in view of further consideration of the prior art teachings, it is determined that there is no strong motivation or reasoning to combine the references to arrive at the claimed invention of claim 20.
Thus, the prior art does not disclose the aforementioned limitation of claim 20.
With regards to claim 21, Wang (WO 2020/190772) discloses a method for providing an encoded representation of parameters of a neural network (paragraph 47), wherein the method comprises:
acquiring a re-ordered multidimensional array using a reordering (paragraph 47);
wherein the method comprises encoding the reordered multi-dimensional array (paragraph 47).
Kang (US 2023/0269399) discloses a method for providing an encoded representation of parameters of a neural network (paragraph 28), wherein the method comprises: in which a given dimension of a given multi-dimensional array of neural network parameters is rearranged to a first dimension in the re-ordered multidimensional array (paragraph 66).
The prior art, either singularly or in combination, does not disclose the limitation “…wherein the method comprises encoding a list of skipped rows; wherein the method comprises encoding neural network coefficients of the reordered multidimensional array at respective positions described by respective sets of array indices; wherein the method comprises deciding, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the reordered multidimensional array, whether to encode or not a neural network parameter at a current position” of claim 21.
Note that prior arts were found and applied above for claim 21. However, in view of further consideration of the prior art teachings, it is determined that there is no strong motivation or reasoning to combine the references to arrive at the claimed invention of claim 21.
Thus, the prior art does not disclose the aforementioned limitation of claim 21.
With regards to claim 22, Wang (WO 2020/190772) discloses a non-transitory digital storage medium having a computer program stored thereon (paragraph 56) to perform the method for providing decoded parameters of a neural network (paragraph 174) on the basis of an encoded representation (paragraph 47), wherein the method comprises:
acquiring a first multi-dimensional array (paragraph 47) comprising a plurality of neural network parameter values using a decoding of neural network parameters (paragraph 80);
wherein the method comprises acquiring a re-ordered multidimensional array using a reordering (paragraph 47),
when said computer program is run by a computer (paragraph 56).
Kang (US 2023/0269399) discloses a non-transitory digital storage medium having a computer program stored thereon (paragraph 177) to perform the method for providing decoded parameters of a neural network on the basis of an encoded representation (paragraph 74), wherein the method comprises: in which a first dimension of the first multi-dimensional array is rearranged to a different dimension in the re-ordered multidimensional array (paragraph 84).
The prior art, either singularly or in combination, does not disclose the limitation “…wherein the method comprises decoding a list of skipped rows, wherein the method comprises entering decoded neural network coefficients into the first multidimensional array at respective positions described by respective sets of array indices, wherein the method comprises deciding, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the first multidimensional array, whether to use a default value for a given neural network parameter or whether to determine the given neural network parameter using a decoding” of claim 22.
Note that prior arts were found and applied above for claim 22. However, in view of further consideration of the prior art teachings, it is determined that there is no strong motivation or reasoning to combine the references to arrive at the claimed invention of claim 22.
Thus, the prior art does not disclose the aforementioned limitation of claim 22.
With regards to claim 23, Wang (WO 2020/190772) discloses a non-transitory digital storage medium having a computer program stored thereon (paragraph 56) to perform the method for providing an encoded representation of parameters of a neural network (paragraph 47), wherein the method comprises:
acquiring a re-ordered multidimensional array using a reordering (paragraph 47);
wherein the method comprises encoding the reordered multi-dimensional array (paragraph 47),
when said computer program is run by a computer (paragraph 56).
Kang (US 2023/0269399) discloses a non-transitory digital storage medium having a computer program stored thereon (paragraph 177) to perform the method for providing an encoded representation of parameters of a neural network (paragraph 28), wherein the method comprises: in which a given dimension of a given multi-dimensional array of neural network parameters is rearranged to a first dimension in the re-ordered multidimensional array (paragraph 66).
The prior art, either singularly or in combination, does not disclose the limitation “… wherein the method comprises encoding a list of skipped rows, wherein the method comprises encoding neural network coefficients of the reordered multidimensional array at respective positions described by respective sets of array indices, wherein the method comprises deciding, in dependence on an entry of the list of skipped rows referenced by a current array index of the first dimension of the reordered multidimensional array, whether to encode or not a neural network parameter at a current position” of claim 23.
Note that prior arts were found and applied above for claim 23. However, in view of further consideration of the prior art teachings, it is determined that there is no strong motivation or reasoning to combine the references to arrive at the claimed invention of claim 23.
Thus, the prior art does not disclose the aforementioned limitation of claim 23.
Conclusion
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLEN C WONG whose telephone number is (571)272-7341. The examiner can normally be reached on Flex Monday-Thursday 9:30am-7:30pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sath V Perungavoor can be reached on 571-272-7455. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALLEN C WONG/Primary Examiner, Art Unit 2488