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 statements (IDS) submitted on 1/29/2024 and 10/16/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements have been considered by the examiner.
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 (i.e., changing from AIA to pre-AIA ) 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.
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 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, 2, 4, 6, 7, 14 are rejected under 35 U.S.C. 103 as being unpatentable over US PGPub 2023/0394651 to Li et al in view of CN111652259A, hereinafter referred to as “CN’259.” It is noted any citation (e.g. pages, line numbers) to CN’259 in the below claim rejections is based upon the supplied English translation of CN’259.
With regard to claim 1, Li et al discloses a device for data cleansing, including: a transceiver 13; and a processor 15, coupled to the transceiver 13 (see [0035]), wherein the processor 15 receives an image through the transceiver, wherein the image includes a picture (“image to be tested” [0035]); and the processor determines that a continuous value corresponding to the image is greater than a continuous value threshold (see [0039] - [0040] the “continuous value” is the generated anomaly score and compared to an anomaly score threshold, and when exceeded, indicates the image to be tested is defective).
However, Li et al fails to disclose that when the threshold is exceeded, the processor performs a global continuity detection on the picture to obtain a gradient distribution value corresponding to the picture and the processor uses the gradient distribution value to determine whether to perform a data cleansing corresponding to a training set on the picture.
CN’259 discloses, in the same field of endeavor (data cleansing for machine learning), a process for determining whether or not to clean original picture data. On page 5, step S4 and step S5, CN’259 sets forth that for each picture that is determined to need further data cleaning, a confidence level is attributed and placed in ranking order from greatest to least (i.e. a gradient distribution) so as to determine whether data cleansing is needed.
It would have been obvious before the effective filing date of the claimed invention to have provided the detected anomalous images of Li et al with further data cleansing as taught by CN’259 as doing this would expand the number of images used in the training data set while maintaining a confidence level that the training data is clean and accurate for its intended training purposes, see CN’259 at the bottom of page 1, “Summary of the Invention.”
With regard to claim 2, the device of claim 1, wherein the continuous value threshold is 0.75. Li et al teaches in [0040] that a suitable anomaly score threshold can be adjusted depending on circumstances and experience. Absent evidence that the 0.75 claimed threshold is result critical, the selection of a threshold suitable for the purposes of the anomaly detection would have been obvious to one having ordinary skill in the art. Furthermore, determining the optimal values of result effective variables would have been obvious and ordinarily within the skill of the art. In re Boesch, 617 F.2d 272, 276, 205 USPQ 215, 219 (CCPA 1980).
With regard to claim 4, the device of claim 1, wherein when the processor determines that the continuous value is not greater than the continuous value threshold, the processor does not add the picture to the training set. See Li et al at [0039] where an image with an anomaly score below the threshold is considered normal, and would thus not need to be processed further by adding to a training set.
With regard to claim 6, the device of claim 1, wherein when the processor determines that the gradient distribution value is a mode, the processor adds the picture to the training set. See CN’259 at page 5, under step S5, lines 6-7, a confidence score in between a first threshold and a second threshold (the scores in-between the upper and lower thresholds is considered the mode) is a sample needing to be confirmed, and is thus further processed.
With regard to claim 7, the device of claim 1, wherein when the processor determines that the gradient distribution value is an extreme number, the processor does not add the picture to the training set. See CN’259 at page 5, under step S5, lines 3 and 4, a confidence score lower than the first confidence level (i.e. an extreme score) indicates the data is negative sample data and is thus deleted.
Claim 14 is rejected for reasoning, mutatis mutandis, as that of claim 1 above.
Allowable Subject Matter
Claims 3, 5, 8-13, 15-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art cited discloses the general state of the art surrounding the cleaning of data used to train machine learning models.
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DAVID OMETZ
Primary Examiner
Art Unit 2672
/DAVID OMETZ/Primary Examiner, Art Unit 2672