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 .
DETAILED ACTION
The action is in response to claims dated 4/23/2024
Claims pending in the case: 1-8, 10-16
Cancelled claims: 9, 17-18
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 10-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Independent claim 10-15 recites a “A convolutional neural network structure for..”. However, such neural network is software per se. There is no associated structural component within the claimed limitations, and as such the claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter.
All claims dependent on this/these claims, is/are also rejected due to their direct or indirect dependencies.
Claims 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Regarding claims 16, these claims are for A computer-readable storage medium comprising a stored program to perform various functions. However, the computer readable media could be interpreted as signals. Therefore, the claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter.
Examiner suggests using the term “non-transitory” to overcome this rejection.
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 (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 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.
Claim(s) 1-3, 7-8, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rao (US 20230091667) in view of Zhang (CMNet: A Connect-and-Merge Convolutional Neural Network for Fast Vehicle Detection in Urban Traffic Surveillance).
Please refer to the attached documents for claim mapping.
Regarding Claim 1, Rao teaches, a quantization aware training method for a convolutional neural network to be executed by an electronic device, the method comprising:
performing sample training on a first convolutional neural network (Rao: [25, 27, 29, 38]: train a first neural network), wherein at least one convolution layer of the first convolutional neural network comprises a mergeable branch structure … (Rao: [68]: layers for deletion and merger);
… in the at least one convolution layer of trained first convolutional neural network, and merging the mergeable branch except the at least one first shortcut in the at least one convolution layer, and obtaining a second convolutional neural network having a first shortcut structure (Rao: [68-69]: The first neural network may be modified using deletion and merging in layers to generate the candidate neural network); and
performing quantization aware training based on the second convolutional neural network (Rao: Fig. 3B, [79]: perform quantization aware training on the candidate neural network);
Although Rao does not recite, shortcut, it would have been obvious to one skilled in the art that a shortcut connection may be used in convolutional neural networks.
Rao does not specifically teach,
at least one first shortcut;
reserving the at least one first shortcut …, and obtaining a second convolutional neural network having a first shortcut structure;
Zhang teaches, at least one first shortcut; reserving the at least one first shortcut …, and obtaining a second convolutional neural network having a first shortcut structure (Zhang: Fig. 3, Pg. 72663 col 2 – Pg. 72664 col 1: connect and merge uses merging and a reserved shortcut as illustrated in the figure);
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Rao and Zhang because the combination would enable using shortcut structures along with merging in the candidate neural network taught in Raso. One of ordinary skill in the art would have been motivated to combine the teachings because the combination would “improve the information flow of the framework and make it easy to train” (see Zhang Abstract).
Regarding Claim 2, Rao and Zhang teach the limitations as claimed in claim 1 and, wherein the at least one first shortcut comprises a shortcut added in the first convolutional neural network, and/or an existing shortcut in the mergeable branch structure (Zhang: Fig. 3, Pg. 72663 col 2 – Pg. 72664 col 1: shortcut structure in the mergeable branch).
Regarding Claim 3, Rao and Zhang teach the limitations as claimed in claim 1 and, wherein if the at least one first shortcut comprises at least one shortcut added in the first convolutional neural network, the at least one shortcut is added in a way of:
for at least one convolution layer with a same input data dimension and output data dimension in the first convolution neural network, taking a result output from a previous convolution layer adjacent to this convolution layer as the at least one shortcut of this convolution layer, performing a first accumulation operation of this convolution layer on the at least one shortcut of this convolution layer and a result output from an activation function operation of this convolution layer, and inputting a result of the first accumulation operation to a next convolution layer adjacent to this convolution layer (Zhang: Fig. 3, Pg. 72663 col 2 – Pg. 72664 col 1: input and output connections explained).
Regarding Claim 7, Rao and Zhang teach the limitations as claimed in claim 1 and, wherein the mergeable branch structure comprises a residual branch and/or a second shortcut (Zhang: Fig. 3, Pg. 72663 col 2 – Pg. 72664 col 1: residual branch),
for each convolution layer, a convolution operation is performed on input data, a second accumulation operation is performed on a result output from the convolution operation and the residual branch and/or the second shortcut, and an activation function operation is performed on a result output from the second accumulation operation (Zhang: Fig. 3, Pg. 72663 col 2 – Pg. 72664 col 1: convolution operation explained).
Regarding Claim 8, Rao and Zhang teach the limitations as claimed in claim 7 and, wherein the at least one first shortcut [[is]] comprises the second shortcut in the mergeable branch structure (Zhang: Fig. 3, Pg. 72663 col 2 – Pg. 72664 col 1: first and second shortcuts in mergeable structure).
Regarding Claim(s) 16, this/these claim(s) is/are similar in scope as claim(s) 1. Therefore, this/these claim(s) is/are rejected under the same rationale.
Claim Rejections using prior art
For Claim(s) 10-15, no prior art was found to teach or make obvious all the limitations as claimed. Since the prior arts fail to disclose, suggest or teach all the claimed limitations, prior art rejection has not been presented.
Potentially Allowable Subject Matter
Claim(s) 4-6 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form in its entirety including all of the limitations of the base claim and any intervening claims, having addressed and corrected any other objections and rejections presented for the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure in the attached 892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANDRITA BRAHMACHARI whose telephone number is (571)272-9735. The examiner can normally be reached Monday to Friday, 11 am to 8 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tamara Kyle can be reached at 571 272 4241. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Mandrita Brahmachari/Primary Examiner, Art Unit 2144
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