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 .
Response to Amendment
The amendments, filed 11/12/2025, have been entered and made of record. Claims 1-11 and 13-15 are pending.
Response to Arguments
Applicant's arguments filed 11/12/2025 have been fully considered but they are not persuasive. See the reasons sets forth below.
In regard to the rejection under 35 U.S.C. 101, applicant states, “…. Applicant's Claim 1 constitute an improvement that sufficiently limits Applicant's Claims preemptive effect. Applicant respectfully submits that they do. For example, Applicant respectfully point out that Applicant's Specification describes that a line camera does not acquire single rectangular images but generates a constant stream of vectors with relatively high resolutions (Paragraph 5 of the Specification as Published). Evaluating such high resolutions with the chipsets for the mobile market is impossible (Paragraph 6). The teachings of the present disclosure provide various solutions for improving deep learning inference of optical inspections in the field of industrial automation. Applicant submits that in the imaging of physical objects, as recited in Claim 1, the resulting optical inspection is run faster than existing inspections. Applicant respectfully submits that Enfish, LLC V. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) informs: if the focus of a claim is on a technological improvement, such as to a computer simulation, the claim is patent-eligible subject matter and there is no need to evaluate step two….”
In response, the Examiner respectfully disagrees. Applicant fails to point out where in the claims is the said “technical improvement” recited or the said “various solutions for improving deep learning inference inspection” is recited. The claims still lack the technical improvement and the rejection is maintained.
Applicant sates, “The current rejection of Independent Claim 1 as previously presented argues Chentanez teaches generating a line-wise image of pixels by a line-camera scanning an object, citing paragraphs 239, 146, and 175 (Office Action, Page 7). None of these paragraphs, however, describe scanning an object to generate a line-wise image of pixels.”
In response, the Examiner respectfully disagrees. On page 2 of the specification, the present application discloses “… in industrial applications much higher resolutions are necessary to fulfill the intended task. This is especially true in the context of continuous production, e.g., in steel production, inspection of fabric, inspection of paper and printing products, or when objects are transported on a conveyor belt and should be analyzed continuously without stopping the conveyor. In the latter case, the predominant image sensor is a so-called line camera. … A line camera does not acquire single rectangular images but generates a constant stream of vectors (dimensionality: spatial resolution of the line-scan x color bands: greyscale: 1 or RGB: 3), on a wide but extremely narrow sensor. Typical resolutions are from 2048 x 1 px up to 12288 x 3 px. However, the line frequency can easily go up to 50khz. Hence, a line camera of 2048 x 1 px and a line frequency of 1 kHz generates an image of 2048 x 1000 px per second. For product and quality inspection tasks such high resolutions are necessary.”
Similarly, Chentanez teaches using a variety of cameras capable of scanning an object continously (see paragraphs 0146-0153). In paragraph 0146, the applied prior art discloses ‘[i]n at least one embodiment, camera types for cameras may include, but are not limited to, digital cameras that may be adapted for use with components and/or systems of vehicle 1900. ... In at least one embodiment, color filter array may include a red clear clear clear (“RCCC”) color filter array, a red clear clear blue (“RCCB”) color filter array, a red blue green clear (“RBGC”) color filter array, a Foveon X3 color filter array, a Bayer sensors (“RGGB”) color filter array, a monochrome sensor color filter array, and/or another type of color filter array. In at least one embodiment, clear pixel cameras, such as cameras with an RCCC, an RCCB, and/or an RBGC color filter array, may be used in an effort to increase light sensitivity.” Paragraph 0239 discloses receiving periodic updates from the vehicle, such as a sequence of images and/or objects. Therefore, the cameras in the applied prior art are cable of scanning an object and generating a line-wise image of pixels.
Applicant states, “Chentanez and especially the passages cited in the Office Action ("paragraphs 0578, 0581, 0584") deal with the training of a neural network, but not with inference. In that context, the passages describe that model training may include retraining or updating an initial model using new training data. The initial model might be a pre-trained model and it might have previously fine-tuned parameters from prior training. Those available parameters are not necessarily re-trained so that "training or retraining 4514 may not take as long or re-quire as much processing as training a model from scratch". In so far, those citations concern "using results of previous calculations instead of repeating calculation." However, Chentanez does not indicate or suggest to re-use in the context addressed in the claims - calculations of pixels from data of a line- camera. As mentioned above, Chentanez deals with faster training, while the claimed subject matter addresses accelerated inference….”
In response, the Examiner respectfully disagrees. As applicant noted, Chentanez teaches “using results of previous calculations instead of repeating calculations.” The claims recite, “using results of previous calculations instead of repeating a calculation of a value of a pixel in a following layer.” In addition, paragraph 0586 of the applied prior art discloses using inference and/or training logic to construct neural network to solve problems. Paragraph 0587 discloses returning inference results of a segmented organ or abnormality. Paragraph 0588 discloses inference and/or training logic are used to perform inferencing and/or training operations associated with one or more embodiments.
Therefore, the Examiner believes that the applied prior art teaches the claimed invention.
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 1-11 and 13-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The Supreme Court has long held that “[l]aws of nature, natural phenomena, and abstract ideas are not patentable.” Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014) (quoting Assoc. for Molecular Pathology v. Myriad Genetics, Inc., 133 S. Ct. 2107, 2116 (2013) (internal quotation marks omitted)). The “abstract ideas” category embodies the longstanding rule that an idea, by itself, is not patentable. Alice Corp., 134S. Ct. at 2355 (quoting Gottschalk v. Benson, 409 U.S. 63, 67 (1972).
In Alice, the Supreme Court sets forth an analytical “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas [or mental processes1] from those that claim patent-eligible applications of those concepts.” Id. at 2355 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1296–97 (2012)). The first step in the analysis is to “determine whether the claims at issue are directed to one of those patent-ineligible concepts.” Id. If the claims are directed to a patent-ineligible concept, the second step in the analysis is to consider the elements of the claims “individually and ‘as an ordered combination’” to determine whether there are additional elements that “‘transform the nature of the claim’ into a patent-eligible application.” Id. (quoting Mayo, 132 S. Ct. at 1298, 1297). In other words, the second step is to “search for an ‘inventive concept’—i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself’”. Id. (brackets in original) (quoting Mayo, 132 S. Ct. at 1294). The prohibition against patenting an abstract idea “‘cannot be circumvented by attempting to limit the use of the formula to a particular technological environment’ or adding ‘insignificant post-solution activity.’” Bilski v. Kappos, 561 U.S. 593, 610–11 (2010) (citation omitted).
In applying the framework set out in Alice, examiner found Applicant’s claims 1-13 are directed to a patent-ineligible abstract concept of performing calibrating the orientation of a camera.
Claim 1 recites: “generating a line-wise image consisting of pixels by a line-camera scanning an object; for each generated new pixel-line, for calculations in the current layer, which do not involve the new pixel-line, using results of previous calculations instead of repeating calculation of a value of a pixel in the next layer.” Calculations in the current layer as claimed is concept performed in human mind including human performing an observation of the captured images, evaluating the acquired image, judgment and/or opinion of the acquired images. These judicial exceptions are not integrated into a practical application. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The claim also does not include details showing improvements in a particular technical field or providing a technical solution to a technical problem. The lack of detail makes the Claims very broad such that the claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The Claims need meaningful limitations that go beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, the steps are all abstract and the Claim as a whole is abstract. CyberSource Corp. 654 F.3d at 1372. “[M]ental processes–or processes of human thinking–standing alone are not patentable even if they have practical application.” In re Comiskey, 554 F.3d 967, 979 (Fed. Cir. 2009); see also Gottschalk v. Benson, 409 U.S. 63, 67 (1972) (“Phenomena of nature . . . , mental processes, and abstract intellectual concepts are not patentable, as they are basic tools of scientific and technological work.” (emphasis added)). The claims are directed to subject matter comprised within its scope an abstract idea “of itself” without significantly more than what is conventional and well-known within the industry.
Claim 9 recites an arrangement for accelerating deep learning inference. Claim 9 is also rejected for the same reason and using the same analysis as discussed in claim 1 above.
Claims 2-8, 10-11 and 13-15 are rejected using the same analysis as discussed in claim 1 above. The dependent claims do not include additional elements to amount to significantly more that an abstract idea. The claims also inherit the deficiency of claim 1, and thereby are rejected under such.
Claim Rejections - 35 USC § 102
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 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.
Claims 1-11 and 13-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Chentanez et al. (US PG PB 2022/0051094 hereinafter referred as Chentanez).
Regarding claim 1, Chentanez discloses a method for accelerating deep learning inference of a neural network with layers (see paragraph 0085 one or more layers from neural network; see paragraph 0169 deep learning accelerator; a CNN for object identification using data from camera sensor), the method comprising:
generating a line-wise image consisting of pixels by a line-camera scanning an object line-by line (see paragraph 0239 sequence of images; see paragraph 0146 image capture camera; see paragraph 0175 execute algorithm on sequential images);
for each generated new pixel-line, for calculations in a corresponding layer, which do not involve the new pixel-line, using results of previous calculations instead of repeating calculation of a value of a pixel in a following layer (see figure 49A and paragraphs 0578, 0581, 0584 updating an initial model; not training model from scratch; pre-trained model is to be updated, retrained, and/or fine-tuned, and pre-trained model may be referred to as initial model; model training to generate refined model). See also the reasons discussed above.
Regarding claim 2, Chentanez discloses removing an oldest pixel-line and associated calculations if an associated input size of the neural network is constant, for each new pixel line (see paragraphs 0109 and 0111).
Regarding claim 3, Chentanez discloses the neural network comprises a convolutional neural network; and calculating the pixels of a given layer includes using a convolution kernel (see paragraphs 0069 and 0483).
Regarding claim 4, Chentanez discloses for each layer: initializing a first-in-first-out buffer unit with at least a size of the vertical resolution of the respective layer minus one; for initialization, putting a following line of the image in the buffer unit until a horizontal resolution of the convolutional kernel is reached; for each line in the respective layer: adding the line to the buffer unit, calculating a convolution on a content of the buffer unit, whereby previously calculated values are stored for the next line, and providing the calculated convolution on the content to a following layer (see paragraphs 0347-0348, 0350, 0353 and 0434).
Regarding claim 5, Chentanez discloses the object comprises a part processed in a production process in a factory (see paragraphs 0140 and 0473).
Regarding claim 6, Chentanez discloses the line-camera is set-up in production line (see paragraphs 0146 and 0150-0151).
Regarding claim 7, Chentanez discloses a stride of the neural network is set to a whole integer greater than one, therefore in one iteration step multiple lines from an input calculate only one output (see figures 6, 17, 34, 40B and 45; and paragraphs 0331 and 0466).
Regarding claim 8, Chentanez discloses performing the method for every color channel of the line-camera (see paragraphs 0103, 0458, 0469, 0495).
Regarding claim 9, the limtiaotn of claim 9 can be found in claim 1 above. Therefore, claim 9 is analyzed and rejected for the same reasons as discussed in claim 1 above.
Claims 10-11 and 13-15 are rejected for the same reason as discussed in claims 2-3 and 5-7 respectively above.
Conclusion
THIS ACTION IS MADE FINAL. 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 HELEN SHIBRU whose telephone number is (571)272-7329. The examiner can normally be reached M-TR 8:00AM-5:00PM.
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/HELEN SHIBRU/Primary Examiner, Art Unit 2484 March 14, 2026
1 See Gottschalk v. Benson, 409 U.S. 63, 67 (1972) (“Phenomena of nature, though just discovered, mental processes, and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work.”). (Emphasis added).