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 .
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 10/8/2024, 12/9/2025, 12/30/2025, and 6/5/2026 is/are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) has/have been considered by the examiner.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claims 5 and 11 objected to because of the following informalities:
Claim 5 line 5-6 “in the in response to” should be “in response to”
Claim 11 line 3 “labele” should be “label”. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
An abnormality diagnosis apparatus …. Configured to receive …and to diagnose …in claim 23. Structural support is found in ¶115-129 and Fig. 11.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
Claims 1-14, 16-18, 20-21 and 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (a mental process) without significantly more. The flow chart in MPEP 2106, Subject Matter Eligibility Test For Products and Processes, will be referred to establish ineligible subject matter.
Regarding claim 1, Step 1: The claim(s) recite(s) “an abnormality diagnosis apparatus” which would be categorized as a product under the 4 statutory categories. See MPEP 2106.03. Step 2A Prong One: However, the claim is further directed to an abstract idea (a mental process) of diagnose an abnormality in the inspection object. Finding an abnormality in an image can be done mentally. See MPEP 2106.04 subsection II and 2106.04(a)(2) subsection III. Step 2A Prong Two: Additional elements include computer elements (a processor and a memory), receiving an image, and a pre-trained artificial intelligence-based diagnosis model. With regards to the computer elements MPEP 2106.04 (A2) III. Metal Process establishes that the addition of a generic computer-implemented steps does not integrate the judicial exception into a practical application. With regards receiving an image this is mere data gathering, which in MPEP 2106.05(g) (3) is insignificant extra-solution activity. See MPEP 2106.04(d) With regards to a pre-trained artificial intelligence-based diagnosis model, this is claimed so generically that it amounts to software on a generic computer (i.e. generic computer implemented step) and therefore does not integrate the judicial exception into a practical application. Step 2B: The additional claim elements do not amount to significantly more than the judicial exception. With regards to the computer elements and a pre-trained artificial intelligence-based diagnosis model MPEP 2106.04 (A2) III. Metal Process establishes that the addition of a generic computer- implemented steps does not integrate the judicial exception into significantly more. With regards to receiving an image this is mere data gathering, and is claimed in a way that is well understood, routine, and conventional. See MPEP 2106.05. Therefore, the claim is not eligible subject matter. Claims 12 and 23 have similar limitations and are not eligible for similar reasons.
Regarding claims 2-11, 13-14, 16-18 and 20-21, additional limitations do not amount to significantly more than the judicial exception and therefore the claims are all ineligible.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 12 and 23 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 2 and 10 of copending Application No. 18834872 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because the claimed invention of Application No. 18834872, obviously encompasses the present claimed invention and differ only in the terminology [Application No. 18834872is narrower than the present application].
Accordingly, in respect to above discussions, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teachings of claims 2 and 10 in Application No. 18834872 as general teachings for an apparatus, a method and a system for receiving image data about an inspection object and diagnosing an abnormality in the inspection object using the received image and a pre-trained artificial intelligence-based diagnosis model as claimed by the present application. The claimed invention of Application No. 18834872 obviously encompasses the present claimed invention.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Claim1, 12, and 23 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 12546725B2. Although the claims at issue are not identical, they are not patentably distinct from each other because the claimed invention of ‘725 U.S. Patent obviously encompasses the present claimed invention and differ only in the terminology [‘725 U.S. Patent is narrower than the present application].
Accordingly, in respect to above discussions, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the teachings of claim 1 in ‘725 U.S. Patent as general teachings for an apparatus, a method and a system for receiving image data about an inspection object and diagnosing an abnormality in the inspection object using the received image and a pre-trained artificial intelligence-based diagnosis model as claimed by the present application. The claimed invention of ‘725 U.S. Patent obviously encompasses the present claimed invention.
Claim Rejections - 35 USC § 102
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(s) 1, 3-7, 9, 12, 14, 16-17, 20 and 23 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bakhshmand (Pub. No. WO 2022160040A1 from applicant’s admitted prior art).
Regarding claim 1, Bakhshmand discloses An abnormality diagnosis apparatus located within a factory monitoring system, the apparatus comprising: at least one processor; memory having programmed thereon instructions that, when executed, are configured to cause the at least one processor to: (Bakhshmand ¶19; inspection of an article utilizing a processor and memory are disclosed.¶66 discloses computer executable instructions. ¶198 discloses utilization of the model in a manufacturing facility environment.) receive image data about an inspection object from an image sensor; and (Bakhshmand ¶85-86, Fig. 3; a camera captures images of an article) diagnose an abnormality in the inspection object using the received image data and a pre-trained artificial intelligence-based diagnosis model. (Bakhshmand ¶114; defects are detected using an object detection model. ¶151 and 161 object detection model is a trained CNN. See also Fig. 3 and 5 for overall model structure.)
Regarding claim 3, Bakhshmand discloses the claim limitations with regards to claim 1, as described above. Bakhshmand further discloses wherein the artificial intelligence- based diagnosis model is pre-trained to output, based on the received image data for the inspection object, diagnostic result data including one or more of whether the inspection object is abnormal, a position where the abnormality occurs, and a type of the abnormality. (Bakhshmand ¶151-153; the model outputs OK label if no defect is present and NG label if a defect is present. When a defect is detected the model further outputs an object class (abnormality type), and location.)
Regarding claim 4, Bakhshmand discloses the claim limitations with regards to claim 1, as described above. Bakhshmand further discloses wherein the abnormality in the inspection object is determined and output as diagnostic result data based on a comparison of predefined normal pattern data with(Bakhshmand ¶203-205 differences in feature maps between the golden sample and the inspection image are used to detect location of defects.
Regarding claim 5, Bakhshmand discloses the claim limitations with regards to claim 4, as described above. Bakhshmand further discloses wherein the instructions are further configured to cause the at least one processor to calculate-an error score based on the comparison of the normal pattern data(Bakhshmand ¶203-205 differences in feature maps between the golden sample and the inspection image are used to detect location of defects.. Centroid/shape analysis thresholds the feature map differences and outputs pixel coordinates.)
Regarding claim 6, Bakhshmand discloses the claim limitations with regards to claim 1, as described above. Bakhshmand further discloses wherein the instructions are further configured to cause the at least one processor to compare the received image data with pre-stored standard image data; correct a position of a region of interest defined as at least a part of the received image data based on the comparison; and diagnose whether the abnormality exists in the inspection object based on the position of the corrected region of interest. (Bakhshmand ¶244; preprocessing step of image registration is disclosed between the inspection (received image) and the golden sample image.)
Regarding claim 7, Bakhshmand discloses the claim limitations with regards to claim 1, as described above. Bakhshmand further discloses wherein the instructions are further configured to cause the at least one processor to compare the received image data with pre-stored standard image data; derive a correction function for converting the received image data into the pre-stored standard image data based on the comparison (Bakhshmand ¶277 adjusting the resolution to match the requirements of the respective network is disclosed.) correct the received image data using the derived correction function; and input the corrected image data into the artificial intelligence-based diagnosis model. (Bakhshmand ¶277 adjusting the resolution to match the requirements of the respective network is disclosed.)
Regarding claim 9, Bakhshmand discloses the claim limitations with regards to claim 5, as described above. Bakhshmand further discloses wherein the instructions are further configured to cause the at least one processor to: determine that the inspection object is in a normal state even if the calculated error score is equal to or more than the predefined threshold in response to the image data being classified as a predefined exception handling type. (Bakhshmand ¶123-124, 128; tolerances for defects are disclosed. A defect maybe found by the object detection component but the PLC may determine that the defect is within tolerance range and determine the image should be labeled OK. The PLC can utilize information from the golden sample component as well. See Fig. 3 and 5 showing overall model structure.)
Regarding claims 12, 14, 16-17, and 20 they have corresponding claim limitations to 1, 3 and 4, 5-6, and 9 respectively and are rejected for similar reasons.
Regarding claim 23 it is the correspond factory monitoring system to claim 1 and is rejected for similar 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, 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) 2 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bakhshmand (Pub. No. WO 2022160040A1 from applicant’s admitted prior art) in view of Miyake (Pub. No. US20180152617A1).
Regarding claim 2, Bakhshmand discloses the claim limitations with regards to claim 1, as described above.
Bakhshmand discloses capturing multiple images (¶86), but not explicitly wherein the instructions are further configured to cause the at least one processor to repeatedly receive image data for the inspection object according to preset time intervals.
Miyake, however, discloses wherein the instructions are further configured to cause the at least one processor to repeatedly receive image data for the inspection object according to preset time intervals. (Miyake ¶12-15; capturing an inspected item at a preset time interval is disclosed.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the apparatus of Bakhshmand with the teachings of Miyake by including capturing images at preset intervals in order to acquire focused image data with a simple and inexpensive configuration (Miyake ¶15).
Regarding claim 13, Bakhshmand discloses the claim limitations with regards to claim 12, as described above.
Bakhshmand discloses capturing multiple images (¶86), but not explicitly wherein receiving image data about the inspection object includes receiving the image data for the inspection object every preset unit time.
Miyake, however, discloses wherein receiving image data about the inspection object includes receiving the image data for the inspection object every preset unit time. (Miyake ¶12-15; capturing an inspected item at a preset time interval is disclosed.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the apparatus of Bakhshmand with the teachings of Miyake by including capturing images at preset intervals in order to acquire focused image data with a simple and inexpensive configuration (Miyake ¶15).
Claim(s) 8 and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bakhshmand (Pub. No. WO 2022160040A1 from applicant’s admitted prior art) in view of Bucher (Pub. No. 20210358110A1).
Regarding claim 8, Bakhshmand discloses the claim limitations with regards to claim 1, as described above.
Bakhshmand does not explicitly disclose wherein the instructions are further configured to cause the at least one processor to: check an operating state of the inspection object; and cancel inputting the received image data into the artificial intelligence- based diagnosis model or to invalidate diagnostic result data output by the artificial intelligence- based diagnosis model in response to the inspection object being in a stationary state.
Bucher, however, discloses wherein the instructions are further configured to cause the at least one processor to: check an operating state of the inspection object; and cancel inputting the received image data into the artificial intelligence- based diagnosis model or to invalidate diagnostic result data output by the artificial intelligence- based diagnosis model in response to the inspection object being in a stationary state. (Bucher ¶26; if a static area has changes in terms of images parameters then an error has occurred in the camera settings, and image-capturing device is not operating fault-free. ¶129 a signaling device can output to a user there is a fault in the system (i.e. Invalidate the result.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the apparatus of Bakhshmand with the teachings of Bucher, by including notifications to the user if the camera settings have an error from Bucher in order to notify a user of unreliable results (Bucher ¶129).
Regarding claim 18, Bakhshmand discloses the claim limitations with regards to claim 12, as described above. Bakhshmand further discloses further comprising: comparing the received image data with pre-stored standard image data; deriving a correction function for converting the received image data into the pre-stored standard image data based on the comparison; (Bakhshmand ¶277 adjusting the resolution to match the requirements of the respective network is disclosed.) correcting the received image data using the derived correction function; inputting the corrected image data into the artificial intelligence-based diagnosis model; (Bakhshmand ¶277 adjusting the resolution to match the requirements of the respective network is disclosed.)
Bakhshmand does not explicitly disclose identifying an operating state of the inspection object; and canceling inputting the received image data into the artificial intelligence-based diagnosis model or invalidating diagnostic result data output by the artificial intelligence-based diagnosis model in response to the inspection object being in a stationary state.
Bucher, however, discloses identifying an operating state of the inspection object; and canceling inputting the received image data into the artificial intelligence-based diagnosis model or invalidating diagnostic result data output by the artificial intelligence-based diagnosis model in response to the inspection object being in a stationary state (Bucher ¶26; if a static area has changes in terms of images parameters then an error has occurred in the camera settings, and image-capturing device is not operating fault-free. ¶129 a signaling device can output to a user there is a fault in the system (i.e. Invalidate the result.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the method of Bakhshmand with the teachings of Bucher, by including notifications to the user if the camera settings have an error from Bucher in order to notify a user of unreliable results (Bucher ¶129).
Claim(s) 10, 11, 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bakhshmand (Pub. No. WO 2022160040A1 from applicant’s admitted prior art) in view of Weiss (Pub. No. US20180300865A1).
Regarding claim 10, Bakhshmand discloses the claim limitations with regards to claim 1, as described above.
Bakhshmand does not explicitly disclose wherein the instructions are further configured to cause the at least one processor to: collect a plurality of image data from a plurality of images, wherein each image of the plurality of images includes a respective inspection object for which a respective abnormality is diagnosed based on the pre-trained artificial intelligence-based diagnosis model; extract feature data from each image of the plurality of images; and cluster the plurality of images into a plurality of clusters based on the extracted feature data.
Weiss, however, discloses wherein the instructions are further configured to cause the at least one processor to: collect a plurality of image data from a plurality of images, wherein each image of the plurality of images includes a respective inspection object for which a respective abnormality is diagnosed based on the pre-trained artificial intelligence-based diagnosis model; (Weiss ¶48-49; defects are detected using a clustering algorithm. (AI diagnosis model). See also Fig. 1, 3 and 4 bottom left, where clusters of features are labeled based on the defect type.) extract feature data from each image of the plurality of images; and cluster the plurality of images into a plurality of clusters based on the extracted feature data. (Weiss ¶58; features are grouped into clusters. )
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the apparatus of Bakhshmand with the teachings of Weiss by including clustering of features and images in order to utilize user feedback in training of the model (Weiss ¶108).
Regarding claim 11, the combination of Bakhshmand and Weiss disclose the limitations with regards to claim 10, as described above. They further disclose wherein the instructions are further configured to cause the at least one processor to: labele each cluster of the plurality of clusters based on defect information input by a user; (Weiss ¶61-62; a user can be prompted to label feature clusters.) and retrain the artificial intelligence-based diagnosis model using the labeled clusters. (Weiss ¶107-109; training and utilizing a classifier to detect defects is disclosed. They system can refine or update (retrain) the classifier. See also ¶113.)
Regarding claim 21, Bakhshmand discloses the claim limitations with regards to claim 12, as described above.
Bakhshmand does not explicitly disclose further comprising: collecting a plurality of image data from a plurality of images, wherein each image of the plurality of images includes a respective inspection object for which a respective abnormality is diagnosed based on the pre- trained artificial intelligence-based diagnosis model; extracting feature data from each image of the plurality of images; and clustering the plurality of images into a plurality of clusters based on the extracted feature data; performing labeling for each of the clusters based on defect type information input by a user; and retraining the artificial intelligence-based diagnosis model using labeled clusters.
Weiss, however, discloses further comprising: collecting a plurality of image data from a plurality of images, wherein each image of the plurality of images includes a respective inspection object for which a respective abnormality is diagnosed based on the pre- trained artificial intelligence-based diagnosis model; (Weiss ¶48-49; defects are detected using a clustering algorithm. (AI diagnosis model). See also Fig. 1, 3 and 4 bottom left, where clusters of features are labeled based on the defect type.) extracting feature data from each image of the plurality of images; and clustering the plurality of images into a plurality of clusters based on the extracted feature data; (Weiss ¶58; features are grouped into clusters. ) performing labeling for each of the clusters based on defect type information input by a user; (Weiss ¶61-62; a user can be prompted to label feature clusters.) and retraining the artificial intelligence-based diagnosis model using labeled clusters. (Weiss ¶107-109; training and utilizing a classifier to detect defects is disclosed. They system can refine or update (retrain) the classifier. See also ¶113.)
It would have been obvious, before the effective filing date of the claimed invention, to one of ordinary skill in the art to modify the method of Bakhshmand with the teachings of Weiss by including clustering of features and images in order to utilize user feedback in training of the model (Weiss ¶108).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEREDITH TAYLOR whose telephone number is (571)270-5805. The examiner can normally be reached M-Th 7:30-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vincent Rudolph can be reached at (571)272-8243. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MEREDITH TAYLOR/Examiner, Art Unit 2671
/VINCENT RUDOLPH/Supervisory Patent Examiner, Art Unit 2671
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