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 4/27/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
RESPONSE TO ARGUMENTS
35 USC 101 Alice
Argument 1
Applicant submits office action incorrectly characterized original claim 6 as identifying parameters and determining weights. Applicant submits Step 2A Prong One Analysis does not match the actual claim language.
In response, examiner submits amended independent claims recite: categorizing check images into OCR-success and OCR-failure groups; associating labels/categorization data; training or further training ML model; receiving a confidence score; comparing the score to a threshold; forwarding an image for OCR; and retraining after OCR failure. Examiner submits claim 1 remains viewed as abstract decision-making framework implemented using generic computer components.
In view of above arguments, examiner submits rejection is sufficient and respectfully maintained.
Argument 2
Applicant submits claims are not mental processes because a human cannot practically train an ML model, operate a confidence model, or perform claimed OCR-confidence workflow in the mind.
In response, examine submits the broader claim is directed to abstract data analysis, classification, prediction, and decision making. The claims organize check image data into categories, associate labels with the data, train or update a predictive model, generate a likelihood score, compare the score against a threshold, route the image based on that score, and update the model based on the OCR outcome. The recited ML model does not remove the claim from the abstract idea category because the claim does not recite a specific ML architecture, a specific training algorithm, a specific feature extraction process, or a specific improvement to how the computer or OCR engine operates. The ML model is used as a generic predictive tool to implement the abstract scoring and routing process.
In view of above arguments, examiner submits rejection is sufficient and respectfully maintained.
Argument 3
Applicant submits that the amendment creates a technical improvement because the first plurality of successfully processed check images include a check image comprising a blurry portion, and because the categorization data includes a label indicating successful OCR processing. Applicant also submits above process permits the model to learn that some blurry images should not be rejected.
In response, examiner submits amended claims do not recite the technical mechanism by which the alleged improvement is achieved. The claims require that the successful OCR training set includes a check image with a blurry portion and that the categorization data includes a success label. However, the claims do not require determining the location of the blurry portion, determining whether the blurry portion overlaps OCR-critical deposit data fields, extracting region specific blur features, weighting blur differently based on image location, modifying OCR processing, modifying OCR processing, modifying image capture or using a particular ML architecture or training rule. As claim does not define a technological improvement in how the computer, OCR engine, image sensor, blue detection process or ML model operates, rejection is sufficient and respectfully maintained.
Argument 4
Applicant submits exception is integrated into a practical application because the trained model reduces false negative image rejection and improves the remote deposit OCR workflow.
In response, generic component completing an abstract process do not integrate the exception into a practical application. Also, examiner submits amended claims do not recite the technical mechanism by which the alleged improvement is achieved.
In view of above arguments, examiner submits rejection is sufficient and respectfully maintained.
Argument 5
Applicant submits claims are more than generic ML because the claims train the model using positive OCR success examples that include blurry portions, rather than treating blur as necessarily disqualifying.
In response, examiner submits the claims simply recite using certain labeled data to train a model and using the model to generate a confidence score. Examiner concludes the claim scope is an abstract process using generic tools.
In view of above arguments, examiner submits rejection is sufficient and respectfully maintained.
Argument 6
Applicant submits claim 20 is statutory subject matter because it recites a non-transitory computer readable device. In response, above does satisfy 101 Alice Test step 1. Examiner submits Steps 2A and 2B are insufficient as the claims are viewed as an abstract idea using generic elements and claims lack technological improvement or inventive concept.
In view of above arguments, examiner submits rejection is sufficient and respectfully maintained.
PRIOR ART REJECTION
The examiner acknowledges the amendment of claims 1-2, 5, 7-17 & 19-24, addition of claims 21-24 and the cancellation of claims 3-4, 6 & 18 filed 04/27/2026. After carefully reviewing applicant amendments, prior art guidance and claim limitations, claim limitations are sufficient to overcome grounds of rejection.
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 1-2, 5, 7-17 & 19-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to as ineligible under subject eligibility test. In the Subject Matter Eligibility Test for Products and Processes (Federal Register, Vol. 79, No. 241, dated Tuesday, December 16, 2014, page 74621), The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional device elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
Claims 1 & 19-20
Step 1
This step inquires “is the claim to a process, article of machine, manufacture or composition of matter?” Yes,
Claim 1 – “Method” is a process.
Claims 19 & 20 - “Systems” or “Non-Transitory CRM” are machines.
Step 2A - Prong 1
This step inquires “does the claim recite an abstract idea, law or natural phenomenon”. This claim appears to directed to an abstract idea.
The limitation of “categorizing a collection of check images into a first plurality of check images that have successfully been processed via optical character recognition (OCR) to obtain deposit data and a second plurality of check images that have failed OCR processing, wherein the first plurality of check images comprises a check image comprising a blurry portion; associating categorization data with each of the first plurality of check images and each of the second plurality of check images, wherein the categorization data associated with each of the first plurality of check images comprises a label indicating an associated image has successfully been processed via OCR to obtain deposit data; providing the first plurality of check images, the second plurality of check images, and the categorization data to an untrained or partially trained machine learning (ML) model to obtain a further trained ML model; providing a deposit check image to the further trained ML model; receiving a confidence score from the further trained ML model, the confidence score indicating a likelihood the deposit check image will be successfully processed via OCR to obtain deposit data; in response to the confidence score meeting a predetermined threshold, forwarding the deposit check image for OCR processing; determining the OCR processing of the deposit check image has failed; in response to the OCR processing of the deposit check image having failed, providing the deposit check image to the further trained ML model to further train the further trained ML model.”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind (e.g. mathematical concepts, mental processes or certain methods of organizing human activity) but for the recitation of generic computer components. That is, other than reciting “at least one memory; and at least one processor coupled to the at least one memory,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “at least one memory; and at least one processor coupled to the at least one memory,” language, “categorizing; associating; providing; receiving; determining” in the context of this claim encompasses covers performance of the limitation in the mind (e.g. mathematical concepts, mental processes or certain methods of organizing human activity).
Step 2A - Prong 2
This step inquires “does the claim recite additional elements that integrate the judicial exception into a practical application”. This judicial exception is not integrated into a practical application. In particular, the claim recites two additional element – using a “at least one memory; and at least one processor coupled to the at least one memory,” to perform “categorizing; associating; providing; receiving; determining” steps. The “at least one memory; and at least one processor coupled to the at least one memory,” are recited at a high-level of generality (i.e., as a generic processor) “categorizing a collection of check images into a first plurality of check images that have successfully been processed via optical character recognition (OCR) to obtain deposit data and a second plurality of check images that have failed OCR processing, wherein the first plurality of check images comprises a check image comprising a blurry portion; associating categorization data with each of the first plurality of check images and each of the second plurality of check images, wherein the categorization data associated with each of the first plurality of check images comprises a label indicating an associated image has successfully been processed via OCR to obtain deposit data; providing the first plurality of check images, the second plurality of check images, and the categorization data to an untrained or partially trained machine learning (ML) model to obtain a further trained ML model; providing a deposit check image to the further trained ML model; receiving a confidence score from the further trained ML model, the confidence score indicating a likelihood the deposit check image will be successfully processed via OCR to obtain deposit data; in response to the confidence score meeting a predetermined threshold, forwarding the deposit check image for OCR processing; determining the OCR processing of the deposit check image has failed; in response to the OCR processing of the deposit check image having failed, providing the deposit check image to the further trained ML model to further train the further trained ML model.” such that it amounts no more than mere instructions to apply the exception using a generic computer component.
STEP 2A – PRONG 2 - CONCLUSION
Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B
The critical inquiry here is does the claim recite additional elements that amount to “significantly more” than the judicial exception? The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a “at least one memory; and at least one processor coupled to the at least one memory,” to perform “categorizing; associating; providing; receiving; determining” steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Dependent Claims
As to claim 2, this claim is directed to generic computer components (“trained ML model”), and insignificant extra-solution activity (“Field of Use/Technological Environment”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 5, this claim is directed to mental process (“providing user instructions to a user”) and insignificant extra-solution activity (“user messaging/remediation – ancillary to abstract decisioning”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 7, this claim is directed to generic computer components (“Deep learning model”), mental process (“identifying parameters and determining weights indicating value e.g. evaluation/judgment”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 8, this claim is directed to generic computer components (“DL model, mobile device”) and insignificant extra-solution activity (“field of use/ environment of use”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 9, this claim is directed to generic computer components (“generic ML model”) and mental process (“updating weights based on other weights e.g. evaluation/optimization”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 10, this claim is directed to mental process (“providing user instructions based on evaluated parameter values e.g. observation/evaluation/judgment and following rules/instructions”) and insignificant extra-solution activity (“ancillary guidance – extra solution activity”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 11, this claim is directed to generic computer components (“onboard sensors”), and insignificant extra-solution activity (“data gathering/adding inputs”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 12, this claim is directed to generic computer components (“onboard sensor, accelerometer, gyroscope”) and insignificant extra-solution activity (“data gathering specificity”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 13, this claim is directed to insignificant extra-solution activity (“narrows what data features are considered however this generally feeds features into the predictive model”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 14, this claim is directed to generic computer components (“onboard sensor, ML model”), and insignificant extra-solution activity (“data gathering/extra inputs”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 15, this claim is directed to mental process (“adjusting a decision threshold based on observed outcomes is evaluation/judgment”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 16, this claim is directed to mental process (“in response to the confidence score meeting the predetermined threshold is core judgment/decision rule”) and insignificant extra-solution activity (“data gathering”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 17, this claim is directed to insignificant extra-solution activity (“data gathering/field of use”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 21, this claim is directed to generic computer components (“generic mobile device, generic processor/memory and generic ML model”) and insignificant extra-solution activity (“implementing the ML on a mobile device merely places the abstract process in a generic mobile computing environment.”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 22, this claim is directed to generic computer components (“processor, generic output/display”), mental process (“if the score fails the threshold, tell the user to retake the image”) and insignificant extra-solution activity (“providing instructions to the user is output/reporting activity ancillary to the abstract confidence score decision.”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 23, this claim is directed to generic computer components (“processor, generic camera, image sensor, generic live stream, image frame capture functionality”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
As to claim 24, this claim is directed to generic computer components (“generic camera or mobile device”) and insignificant extra-solution activity (“manual image capture is data gathering before the abstract ML/OCR confidence workflow”). Thus, this claim does not integrate the abstract idea into a practical application or constitute significantly more than the abstract.
CONCLUSION
No prior has been found for claims 1-2, 5, 7-17 & 19-24 in their current form.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
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
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