DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 02/04/2026 has been entered.
Response to Arguments
Applicant's arguments have been considered but are moot in view of the new ground(s) of rejection in view of Topman (WO 2012/035504 A1), provided by the Applicant in the IDS submitted on 02/04/2026.
Information Disclosure Statement
The information disclosure statement submitted on 02/04/2026 has been considered by the Examiner and made of record in the application file.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claims 1, 3-6 and 12-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Haoguang (“Single Coated Maize Seed Identification Based on Deep Learning”) in view of Topman (WO 2012/035504 A1).
Regarding claim 1, Haoguang discloses a method for processing images of seeds, the method comprising: (abstract, section III paragraph 1)
inputting a seed image comprising at least a portion of a seed to a trained neural network to generate a value associated with the coverage of a coating on the seed; (abstract, figure 2, section III; Haoguang discloses coated and non-coated maize seeds are distinguished based on spectra (derived from image) input into a trained neural network. A method of near infrared spectroscopy qualitative modeling based on deep learning. The determined labels “coated” and “non-coated” are binary values associated with the coating coverage, i.e. existent or non-existent coating coverage).
the trained neural network having been trained to generate a value associated with the coverage of coating on the seed using a plurality of training images each comprising at least a portion of a training seed, and wherein each training image is labelled with a value associated with the coverage of a coating on the training seed, (abstract, page 1523; Haoguang discloses the neural network is trained with a plurality of non-coated seeds. Maize seed spectrum without seed coating agent were used as training set… T1 data set without SCA was choice as training sets, i.e. with a label indicating a non-existent coating coverage.)
wherein a plurality of seed images generated from the same image or taken from the same sample are input to the trained neural network (section II. A. Stack Auto-encoder Neural Networks) but fails to disclose generating a plurality of values associated with the coverage of a coating corresponding to the seed images, and an average of the plurality of values is taken.
In related art, Topman discloses generating a plurality of values associated with the coverage of a coating corresponding to the seed images, (page 16: the cell count is estimated by determining the area covered by the cells in the culture (area of confluency) and dividing by an average size of the cells) and an average of the plurality of values is taken. (pages 16-17: estimating a cell count in said cell culture according to a size of areas occupied by cells and an average size of the cells in said cell concentrations; At 260, the cell count in the culture is optionally estimated by dividing the area of confluency (area covered by cells) by the average size of the cells in the culture. Optionally, the cell count is determined automatically. Optionally, the cell count is determined using a linear regression model. Alternatively, the cell count is determined using a non-linear regression model.)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Topman into the teachings of Haoguang to effectively detect cell occupancy and determining a culture’s confluency or cell count.
Regarding claim 16, Haoguang discloses a method for processing images of seeds, the method comprising: (abstract, section III paragraph 1)
inputting a seed image comprising at least a portion of a seed to a trained neural network to generate a value associated with the coverage of a coating on the seed; (abstract, figure 2, section III; Haoguang discloses coated and non-coated maize seeds are distinguished based on spectra (derived from image) input into a trained neural network. A method of near infrared spectroscopy qualitative modeling based on deep learning. The determined labels “coated” and “non-coated” are binary values associated with the coating coverage, i.e. existent or non-existent coating coverage).
the trained neural network having been trained to generate a value associated with the coverage of coating on the seed using a plurality of training images each comprising at least a portion of a training seed, and wherein each training image is labelled with a value associated with the coverage of a coating on the training seed, (abstract, page 1523; Haoguang discloses the neural network is trained with a plurality of non-coated seeds. Maize seed spectrum without seed coating agent were used as training set… T1 data set without SCA was choice as training sets, i.e. with a label indicating a non-existent coating coverage.)
wherein the trained neural network is trained using first training images of training seeds (section II. A. Stack Auto-encoder Neural Networks) but fails to disclose a coating of a first color, and using second training images of training seeds of a second color.
In related art, Topman discloses a coating of a first color, and using second training images of training seeds of a second color. (page 29)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Topman into the teachings of Haoguang to effectively detect cell occupancy and determining a culture’s confluency or cell count.
Regarding claim 3, Haoguang, as modified by Topman, discloses the claimed invention wherein the value associated with the coverage of the coating on the seed and/or training seed indicates at least one of: the percentage of the seed surface covered in a coating; the uniformity of the coverage of the coating on the seed. (section III; with and without seed coating)
Regarding claim 4, Haoguang, as modified by Topman, discloses the claimed invention wherein the method further comprises the step of training the neural network. (abstract, section II-C; maize seed spectrum without seed coating agent were used as training set)
Regarding claim 5, Haoguang, as modified by Topman, discloses the claimed invention wherein the trained neural network is trained using first training images of training seeds comprising a coating of a first colour, and using second training images of training seeds comprising coatings of a second colour. (page 29)
Regarding claim 6, Haoguang, as modified by Topman, discloses the claimed invention wherein the step of inputting comprises inputting a seed image of a seed comprising a coating of the first colour. (page 29)
Regarding claim 12, Haoguang, as modified by Topman, discloses the claimed invention wherein the neural network is at least one of: a convolutional neural network; and a deep neural network. (title)
Regarding claim 13, Haoguang, as modified by Topman, discloses the claimed invention wherein the neural network comprises at least one of each of: an input layer, a 2D convolution layer, a batch normalization layer, a ReLU layer, a max pooling layer, a fully connected layer, and a regression layer. (abstract, section IIA)
Regarding claim 14, Haoguang, as modified by Topman, discloses the claimed invention wherein computer program which, when executed by a computing system comprising processor hardware and memory hardware, causes the processor hardware to perform the method in claim 1. (abstract, section IIA)
Regarding claim 15, Haoguang, as modified by Topman, discloses the claimed invention wherein an apparatus comprising processor hardware and memory hardware, the memory hardware storing processing instructions which, when executed by the processor hardware, cause the processor hardware to perform the method as claimed in claim 1. (abstract, section IIA)
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claim 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Haoguang in view of Topman and in further view of Yongkui (CN 208270444).
Regarding claim 2, Haoguang, as modified by Topman, discloses the claimed invention except for wherein the value associated with the coverage of the coating on the seed and/or training seed indicates the resistance of the coating to abrasion.
In related art, Yongkui discloses the value associated with the coverage of the coating on the seed and/or training seed indicates the resistance of the coating to abrasion. (paragraphs 20-24)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Yongkui into the teachings of Haoguang and Topman to effectively seed coating qualified rate detection system.
Claims 7-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Haoguang in view of Topman and in further view of Schnier (US 2015/0178948 A1).
Regarding claim 7, Haoguang, as modified by Topman, discloses the claimed invention except for wherein the seed image is generated by extracting a region of a seed from an image comprising a plurality of seeds.
In related art, Schnier discloses the seed image is generated by extracting a region of a seed from an image comprising a plurality of seeds. (paragraphs 36 and 42)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Schnier into the teachings of Haoguang and Topman for effective quality control.
Regarding claim 8, Haoguang, as modified by Topman and Schnier, discloses the claimed invention wherein the region of the seed is extracted using an algorithm to detect circles in images to detect an area within the seed, where the area within the seed is then extracted. (Schnier: paragraphs 36 and 42)
Regarding claim 9, Haoguang, as modified by Topman, discloses the claimed invention except for wherein the training image is generated by extracting a region of a training seed from an image comprising a plurality of training seeds.
In related art, Schnier discloses the training image is generated by extracting a region of a training seed from an image comprising a plurality of training seeds. (paragraphs 36 and 42)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the teachings of Schnier into the teachings of Haoguang and Topman for effective quality control.
Regarding claim 10, Haoguang, as modified by Topman and Schnier, discloses the claimed invention wherein the region of the training seed is extracted using an algorithm to detect circles in images to detect an area within the training seed, where the area within the training seed is then extracted. (Schnier: paragraphs 36 and 42)
Conclusion
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/BOBBAK SAFAIPOUR/Primary Examiner, Art Unit 2665