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
INFORMATION DISCLOSURE STATEMENT
The information disclosure statement (IDS) submitted on 1/8/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
FOREIGN PRIORITY
A claim for foreign priority under 35 U.S.C § 119 (a) - (d), which was contained in the Declaration and Power of Attorney filed on 07/05/2024 has been acknowledged. Acknowledgement of claimed foreign priority and receipt of priority documents is reflected in form PTO-326 Office Action Summary.
CLAIM REJECTIONS - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
As to claims 4, 11 & 18 claim elements “a group of sample feature maps comprises a feature map in a feature map size range of the N feature map size ranges” is a limitation that invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function “a group of sample feature maps comprises a feature map in a feature map size range of the N feature map size ranges”
In this case, the above phrase is unclear to whether each group contains only one feature map from one of the size ranges. Specification [0015, 0017, 0019, 0129-0136] discloses each group as including feature maps across the N feature map size ranges, often as N sample feature maps corresponding to the N ranges.
As to claim 12 claim elements “wherein the one or more processors are configured to perform the plurality of training iterations on the neural network comprises the one or more processors are configured to:” is a limitation that invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function “wherein the one or more processors are configured to perform the plurality of training iterations on the neural network comprises the one or more processors are configured to:”
In this case, the above phrase is unclear (1) whether the processors are performing the training iteration step, (2) what “perform the plurality of training iterations” comprises or (3) is the claim introducing a second, separate processor configuration limitation.
As to claim 13 claim elements “wherein the one or more processors are configured to perform the plurality of training iterations on the neural network comprises the one or more processors are configured ” is a limitation that invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function “wherein the one or more processors are configured to perform the plurality of training iterations on the neural network comprises the one or more processors are configured to:”
In this case, the above phrase is unclear (1) whether the processors are performing the training iteration step, (2) what “perform the plurality of training iterations” comprises or (3) is the claim introducing a second, separate processor configuration limitation.
As to claim 14 claim elements “N sample feature maps obtained from encoded N first sample images, the encoded N first sample images are obtained through a resizing of a second sample image” is a limitation that invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for the claimed function “N sample feature maps obtained from encoded N first sample images, the encoded N first sample images are obtained through a resizing of a second sample image”
In this case, the above phrase does create clarity between images, encoded images, and feature maps. Specification [0020-0023, 0130-0136] discloses the process of (1) resizing a second sample image; (2) obtaining N first sample images; (3) encoding those images; (4) obtaining N sample feature maps. The specification and claim outlay provide a fair bit of lack of clarity.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph; or
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the claimed function, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
As to claims 5-7, 12-14 & 18-20, these claims are rejected due to their dependence on claims 4, 11 & 18 and are rejected for the same reasons.
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 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, 3, 8, 10, 15 & 17 are rejected under 35 U.S.C. 103 as being unpatentable over YOO et al. (U.S. Publication 2021/0279568) in view of BROTHERS (U.S. Publication 2020/0349432) & Wshah (U.S. Publication (U.S. Publication 2017/0372174)
As to claims 1, 8 & 15 YOO discloses invoking a neural network model to process the target feature map, to obtain a processing result of the target feature map; ([0005 discloses extracting a first target feature vector from a target feature map] and generating a first output feature vector of an output feature map. [0016] discloses the target feature map may correspond to an input feature map or a hidden feature map. [0069] discloses the target feature map may be the input feature map 210, Fig. 2 or the hidden feature map 330, Fig. 3. [0107] discloses extracts a first target feature vector from a target feature map an generates a first output feature vector of an output feature map. [0109] discloses extracting a first target feature vector from a target feature map and generate a first output feature vector of an output feature map.),
YOO is silent to wherein the neural network model comprises P dynamic stride modules. and a stride of a dynamic stride module of the P dynamic stride modules is a target stride corresponding to a dynamic stride module in the P target strides.
However, BROTHERS disclose wherein the neural network model comprises P dynamic stride modules. ([0004] discloses a convolutional layer in a convolutional neural network uses a predetermined horizontal input stride and a predetermined vertical input stride that are greater than 1. [0005] discloses a current convolutional layer of the neural network.) and a stride of a dynamic stride module of the P dynamic stride modules is a target stride corresponding to a dynamic stride module in the P target strides. ([0004] discloses predetermined horizontal input stride and predetermined vertical input stride. [0006] discloses predetermined horizontal input stride and predetermined vertical input stride.)
It would have been obvious to one of ordinary skill in the art at the time of effective filing to modify Yoo’s disclosure to include the above limitations in order to provide a stride selected convolutional layer for processing the target feature map rather than restricting the feature map processing operation to only one fixed stride.
YOO in view of BROTHERS is silent to determining P target strides based on a preset correspondence between a stride and a feature map size range and a size of a target feature map.
However, Wshah discloses determining P target strides based on a preset correspondence between a stride and a feature map size range and a size of a target feature map. ([0005] discloses the number of first convolutional layers is based on a first size for the input images. See wherein responsive to an input image being a second size larger than the first size, additional convolutional layers are added to the convolutional neural network. [0033] discloses as the size of the image increases, the number of layers of the CNN must increase as well. Hence, additional modules may be added to the CNN. [0037] discloses the number of first convolutional layers is based on a first size for the input images. Also see wherein responsive to an input image being a second size larger than the first size, additional convolutional layers are added to the convolutional neural network. )
It would have been obvious to one of ordinary skill in the art at the time of effective filing to modify YOO in view of BROTHERS’s disclosure to include the above limitations in order to select which stride setting to use for the stride configured convolutional layer based on the size condition of the feature map input being processed rather than using the same stride setting for all feature map sizes.
As to claims 3, 10 & 17, YOO in view of BROTHERS & Wshah discloses everything as disclosed in claims 1, 8 & 15 respectively but is silent to wherein the dynamic stride module of the P dynamic stride modules is a dynamic stride convolutional layer or a dynamic stride residual block.
However, BROTHERS discloses wherein the dynamic stride module of the P dynamic stride modules is a dynamic stride convolutional layer or a dynamic stride residual block.
([0004] discloses a convolutional layer in a convolutional neural network uses a predetermined horizontal input stride and a predetermined vertical input stride that are greater than 1.)
It would have been obvious to one of ordinary skill in the art at the time of effective filing to modify YOO in view of BROTHERS & Wshah’s disclosure to include the above limitations in order to forgo a residual block implementation.
CONCLUSION
No prior art has been found for claims 2, 4-7, 9, 11-14, 16 & 18-20 in their current form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Stephen P Coleman whose telephone number is (571)270-5931. The examiner can normally be reached Monday-Thursday 8AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Andrew Moyer can be reached at (571) 272-9523. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Stephen P. Coleman
Primary Examiner
Art Unit 2675
/STEPHEN P COLEMAN/Primary Examiner, Art Unit 2675