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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/21/2025, 02/03/2025 was filed and is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 112
Claim 3 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “deviation” in claim 3 is a relative term which renders the claim indefinite. The term “deviation” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The third value depending on this deviation causes the third value to be indefinite.
Claim Rejections - 35 USC § 101
Claim(s) 1-8 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). The claim(s) recite(s) a method, a device, and a non-transitory computer-readable recording medium for abnormality detection. This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 7, 8 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Claim(s) 1, 7, 8 are directed to a non-transitory computer-readable recording medium and a device, i.e. a system, and a method, i.e. process.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? YES , the claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The non-transitory computer-readable recording medium in claim 1, the method in claim 7, and device in claim comprise a mental process that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding Claim(s) 1, 7, 8: the method recites the steps (functions) of:
detect an abnormality in the input scene based on the calculated first and second values (mental process including observation and evaluation, and can be done mentally in the human mind; a human mind can look at the saliency map along with the region outside the detection object to determine an abnormality; a non-limiting, illustrative example are the “Spot the Difference” games);
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 7, 8 does/do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim(s) 1 recite(s) the further limitations of:
A non-transitory computer-readable recording medium having stored therein an abnormality detection program that causes a computer to execute a process (generic computers or components configured to perform the method; instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea);
calculating a first value and a second value, based on a detection result of an object detected from an input scene to an object detection model and a saliency map for the input scene obtained by an XAI technique, the first value indicating a value of the saliency map for the entire input scene, the second value indicating a value of the saliency map in a region other than a region of the detected object in the input scene (generic computers or components configured to perform the method; a non-limiting example is the library TensorFlow that can do both);
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claim(s) 1, 7, 8 does/do not recite any additional elements that are not well-understood, routine or conventional. The use of a computer to storing, calculating, detecting, as claimed in Claim(s) 1, 7, 8 is a routine, well-understood and conventional process that is performed by computers.
Thus, since Claim(s) 1, 7, 8 is/are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1, 7, 8 is/are not eligible subject matter under 35 U.S.C 101.
Regarding claim 2: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): the calculating includes calculating a third value based on the first and second values (mental process including observation and evaluation, and can be done mentally in the human mind; a human mind can roughly calculate an average, difference, summation, and other mathematical methods) OR (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations) OR (insignificant pre/post-solution extra activity of generating data) OR (generic computers or components configured to perform the method); the detecting includes detecting an abnormality in the input scene based on the third value (mental process including observation and evaluation, and can be done mentally in the human mind; a human mind can look at the image and the calculated third value to detect if an abnormality exists, which includes a non-limiting example of explainable AI to determine why a classification occurred by the AI) OR (generic computers or components configured to perform the method; a non-limiting example would be “Spot the Difference” games that have the solution already known, then highlights it for the player).
Regarding claim 3: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the third value is a deviation of the first and second values (mental process including observation and evaluation, and can be done mentally in the human mind; if the third value has any changes from the first and second values, then a human can spot the difference, or deviation of the number) OR (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations) OR (insignificant pre/post-solution extra activity of generating data) OR (generic computers or components configured to perform the method).
Regarding claim 4: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the XAI technique is an activation-based or gradient-based saliency map output technique (generic computers or components configured to perform the method).
Regarding claim 5: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the process further includes generating the saliency map for a layer to which non-maximum suppression (NMS) has been applied, in a one-stage type of the object detection model (generic computers or components configured to perform the method; non-maximum suppression is a well-understood and routine, as PHOSITA would know).
Regarding claim 6: the additional limitations do not integrate the mental process into practical application or add significantly more to the mental process. The limitation(s): wherein the process further includes generating the saliency map for a final layer of a region proposal network (RPN) component in a two-stage type or multi-stage type of the object detection model (generic computers or components configured to perform the method).
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-5, 7, 8 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Szyc (“Checking Robustness of Representations Learned by Deep Neural Networks”, 2021, as cited in IDS filed 07/21/2025).
Regarding claims 1, 7, 8, Szyc teaches A non-transitory computer-readable recording medium (Szyc, pg 401, second full paragraph: “by the training algorithm”. Algorithm is being interpreted as involving “a non-transitory computer-readable recording medium”) having stored therein an abnormality detection program (Szyc, pg 402, lines 3-4: “We used this knowledge to find some natural adversarial examples”. Which is being interpreted as involving “abnormality detection program”) that causes a computer to execute a process ((Szyc, pg 401, second full paragraph: “by the training algorithm”. Algorithm is being interpreted as involving “a computer to execute a process”) comprising:
calculating a first value (Szyc, Figure 1b, which shows the saliency map of the input scene) and a second value (Szyc, Figure 1b and Figure 1c, which shows saliency map includes outside the bounding box), based on a detection result of an object detected (Szyc, see nearest image below, “ROI” is being interpreted as “object detected”) from an input scene (Szyc, see nearest image below, “found in the training and validation data”, which is being interpreted to involve “an input scene”) to an object detection model (Szyc, see nearest image below, “bounding boxes” are being interpreted as non-limiting examples of the usage of an object detection model) and a saliency map (Szyc, see nearest image below, “saliency maps”) for the input scene obtained by an XAI technique (Szyc, see nearest image below, “The saliency maps reveal that majority of the model’s attention”, which is being interpreted as XAI, or explaining what the AI is paying attention to, as a non-limiting explanation), the first value indicating a value of the saliency map for the entire input scene (Szyc, Figure 1b, which shows the saliency map of the input scene), the second value indicating a value of the saliency map in a region other than a region of the detected object in the input scene (Szyc, pg 401, first full paragraph, reproduced below:
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. “The saliency maps reveal that majority of the model’s attention is focused outside the ROI [the rugby ball], and hence the recognition of this image relies primarily [solely?] on the background or surroundings of the object”. “Outside the ROI” is being interpreted as involving “region other than a region of the detected object in the input scene”); and
detecting an abnormality (Szyc, pg 402, lines 3-5: “We used this knowledge to find some natural adversarial examples, which illustrates the low reliability of the models for these categories”) in the input scene based on the calculated first and second values (Szyc, pg 400, Fig. 1 text: “Robustness score is the ratio of saliency map summed within the bounding box (c) and saliency map summed over the entire image (b)”. Which is being interpreted as involving calculation that is based on second and first value, respectively.)
Regarding claim 2, Szyc teaches The non-transitory computer-readable recording medium according to claim 1, wherein
the calculating includes calculating a third value based on the first and second values (Szyc, pg 400, Fig. 1 text: “Robustness score is the ratio of saliency map summed within the bounding box (c) and saliency map summed over the entire image (b)”. Robustness score is being interpreted as involving “third value”.), and
the detecting includes detecting an abnormality in the input scene based on the third value (Szyc, pg 401 [last paragraph] to 402 [lines 1-5], reproduced below:
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. Which shows the high accuracy and low robustness score [third value] allows the authors to find natural adversarial examples, which are interpreted as “abnormality” detection.).
Regarding claim 3, Szyc teaches The non-transitory computer-readable recording medium according to claim 2, wherein the third value is a deviation of the first and second values (Szyc, pg 400, Fig. 1 text: “Robustness score is the ratio of saliency map summed within the bounding box (c) and saliency map summed over the entire image (b)”. Which shows the robustness score [third value] deviates from the first and second value. As the ratio causes a natural deviation, or change, as a non-limiting example).
Regarding claim 4, Szyc teaches The non-transitory computer-readable recording medium according to claim 1, wherein the XAI technique is an activation-based (Szyc, pg 404, paragraph after item 3: “or, in other words, the portion of saliency map activation included within the ROI”. “Activation” is being interpreted as involving “activation-based”) or gradient-based saliency map output technique (Szyc, pg 403, ¶2: “The current approaches rely on gradient backpropagation which is faster and more accurate”. Which is being interpreted as involving “gradient-based saliency map output”).
Regarding claim 5, Szyc teaches The non-transitory computer-readable recording medium according to claim 1, wherein the process further includes generating the saliency map (Szyc, pg 404, last paragraph: “The application of the proposed method for a given dataset requires a saliency map generator and bounding boxes.”) for a layer to which non-maximum suppression (NMS) has been applied (Szyc, pg 404, last paragraph: “However, we think that an object detection method like EfficientDet [25] or YOLO [4] could be useful to generate such boxes automatically”. “YOLO” is being interpreted as involving NMS. As PHOSITA would know is a common post-processing technique after using YOLO. As stated in informative example: YOLOv4: https://arxiv.org/abs/2004.10934), in a one-stage type of the object detection model (Szyc, pg 404, last paragraph: “However, we think that an object detection method like EfficientDet [25] or YOLO [4] could be useful to generate such boxes automatically”. “YOLO” is being interpreted as involving “one-stage type of object detection model”).
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) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Szyc, in view of Vellaichamy (“DetectorDetective: Investigating the Effects of Adversarial Examples on Object Detectors”, 2022).
Regarding claim 6, Szyc teaches The non-transitory computer-readable recording medium according to claim 1, wherein the process further includes generating the saliency map (Szyc, pg 404, last paragraph: “The application of the proposed method for a given dataset requires a saliency map generator and bounding boxes”)
However, Szyc does not appear to explicitly teach “final layer of a region proposal network (RPN) component in a two-stage type or multi-stage type of the object detection model”. Although, Szyc already mentions using different object detector models (pg 404, last paragraph).
Pertaining to the same field of endeavor, Vellaichamy teaches
for a final layer of a region proposal network (RPN) component (Vellaichamy, Abstract, “Region Proposal Network”, which is part of “the three key modules of Faster R-CNN object detector” and involving “a final layer”) in a two-stage type or multi-stage type of the object detection model (Vellaichamy, Abstract, “DetectorDetective enables users to easily learn about how the three key modules of the Faster R-CNN object detector”. “Faster R-CNN” is being interpreted as two-stage type or multi-stage type of object detection model).
Szyc and Vellaichamy are considered to be analogous art because they are directed to the field of explainable AI with object detection and saliency maps. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and system for abnormality detection using object detection and saliency with mention of using different object detection models (as taught by Szyc) to include final layer of a region proposal network (RPN) component in a two-stage type or multi-stage type of the object detection model (as taught by Vellaichamy) because the combination provides education for users to visualize and understand adversarial examples as it travels through an object detection pipeline (Vellaichamy, Abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Sharma et al ("Adversarial Patch Attacks and Defences in Vision-Based Tasks: A Survey”, 2022) discloses abnormality (adversarial patch) and object detection using saliency maps.
Yang et al (“Self-Supervised Surface Defect Localization via Joint De-Anomaly Reconstruction and Saliency-Guided Segmentation”, 2023) abnormality (anomaly) and object detection using saliency maps.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHNNY B DUONG whose telephone number is (571)272-1358. The examiner can normally be reached Monday - Thursday 10a-9p (ET).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at (571)272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.B.D./Examiner, Art Unit 2667 /MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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