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.
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:
a composite thermal image data learning part, in claims 1-7
a composite thermal image data feature extraction part, in claims 1 and 8
a composite thermal image data defect determination part in claim 1
there is no corresponding structure disclosed in the specification, see the 112b and 112a rejections herein below.
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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-8 are 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.
Claim limitations “a composite thermal image data learning part”, “a composite thermal image data feature extraction part”, and “a composite thermal image data defect determination part” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. There is no description of any physical structure in either the claims or the specification, and no inherent structure can be simply assumed to perform the functions. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-8 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding independent claims 1-8, the limitation “a composite thermal image data learning part”, “a composite thermal image data feature extraction part”, and “a composite thermal image data defect determination part” invokes interpretation of the limitation under 112(f), and therefore the specification is turned to for the corresponding structure. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore the claims are rejected under 35 U.S.C. 112(a) for lacking adequate written description because the specification does not describe the claimed invention in sufficient detail that one skilled in the art can reasonably conclude that the inventor had possession of the claimed invention (see MPEP 2185).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over KR 2021-0044080 A to Sang et al., hereinafter, “Sang” in view of US 2019/0003983 A1 to Al-Omari.
Claim 1. Sang teaches A defect detection system using deep neural network based analysis of composite thermal image data, the defect detection system comprising: [0002] a machine learning-based defect classification apparatus and method capable of detecting the location and shape of a defect only by learning defect classification
a composite thermal image data learning part (110) configured to learn composite thermal image data to generate a defect detection model; [0028] a model for extracting a feature map and classifying defects is applied, and this model is a model learned based on machine learning.
a composite thermal image data feature extraction part (120) configured to use the defect detection model to extract features of input thermal image data of an inspection subject composite; [0033] The classification unit 20 performs global average pooling on the feature map output from the feature extraction unit 10, and then performs product defects through a neural network of a fully connected layer. Classify.
and a composite thermal image data defect determination part (130) configured to determine, on the basis of the extracted features, whether the inspection subject composite has a defect. [0050] The binarization unit 36 binarizes the final defect activation map to a specific threshold and outputs a binarized image. In the final defect activation map, the defective part has a relatively large value and the non-defective part has a relatively small value, so based on a specific threshold, the defective part is 1 and the non-defective part is binarized. You can create an image. The location and shape of the defect is detected through the binarized image.
Sang fails to explicitly teach a composite thermal image data, Al-Omari, in the same field of inspecting a composite material structure for defects using a neural network, teaches [0006] a training system including an arrangement for obtaining thermal images from a known composite material sample…an infrared camera for capturing thermal images of the sample when heated…computer system adapted to receive thermal images received from the inspection apparatus and to detect quantitative parameters of defects in the structure using the training database.
[0032] neural network that can be employed in the expert system training method, [0048] and [0074]
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Sang with the teachings of Al-Omari [0005] because there is therefore a need for non-destructive techniques for rapidly, reliably and cost-efficiently inspecting composite structures in an accurate quantitative manner.
Claim 9. Reviewed and analyzed in the same way as claim 1. See the above analysis and rationale.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over KR 2021-0044080 A to Sang et al., hereinafter, “Sang” in view of US 2019/0003983 A1 to Al-Omari and in further view of US 2024/0362762 A1 to Zhang et al., hereinafter, “Zhang”.
Claim 2. Sang fails to explicitly teach a partial feature extraction, Zhang, in the same field of defect detection using a neural network, teaches wherein the composite thermal image data learning part (110) is configured to learn the composite thermal image data on the basis of a deep neural network including a partial thermal gradient feature extraction deep neural network, Zhang [0004] a backbone feature extraction network including a deep residual network (ResNet) 101 and a feature pyramid network, an improved Region Proposal Network (RPN), a region of interest (ROI) pooling layer, a global ROI extraction layer, a bounding-box regression network, and a classification network, where the backbone feature extraction network is configured to extract global features of the image; the improved RPN network and the ROI pooling layer are configured to extract features of the region proposal of the image Examiner interprets region to be partial.
Zhang teaches and a global thermal gradient feature extraction deep neural network. [0004] a backbone feature extraction network including a deep residual network (ResNet) 101 and a feature pyramid network, an improved Region Proposal Network (RPN), a region of interest (ROI) pooling layer, a global ROI extraction layer, a bounding-box regression network, and a classification network, where the backbone feature extraction network is configured to extract global features of the image; the improved RPN network and the ROI pooling layer are configured to extract features of the region proposal of the image
Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Sang with the teachings of Zhang [0005] to solve the technical problems such as high false detection rate, high missed detection rate, and low detection efficiency in defect detection.
Al-Omari teaches a thermal gradient time-series feature extraction deep neural network, [0043] performs a mathematical simulation of how the modeled defects react to heating and which generates virtual thermographs (images indicative of temperature) showing temperature changes of the modeled defects over time, and c) correlates the virtual thermographs with parameters of the modeled defects using a machine learning approach, producing an accessible virtual thermograph database
Allowable Subject Matter
Claims 3-8 and 10-12 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.
The innovation that makes claims 3 and 10 allowable is “generate multiple particular-sized split sections not overlapping from thermal image data for training, and extract and input a particular split section of the split sections to the partial thermal gradient feature extraction deep neural network to extract multiple feature maps, and input the extracted multiple feature maps to the thermal gradient time-series feature extraction deep neural network”.
Likewise claims 4-8 and 11-12 are allowed because they are dependents of claims 3 and 10, respectively.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DELOMIA L GILLIARD whose telephone number is (571)272-1681. The examiner can normally be reached 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Villecco can be reached at (571) 272-7319. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DELOMIA L GILLIARD/Primary Examiner, Art Unit 2661
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