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 submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement(s)
The Information disclosure statement (IDS) filed on April 11th, 2024 has been acknowledged and considered by the examiner.
Claim Objections
Claim 10 is objected to because of the following informalities:
Claim 10’s reference “the method of claim 6” should be read as “the apparatus of claim 6” to follow antecedent basis and avoid 112f indefiniteness issue. Appropriate correction is required.
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 limitations are:
1) “a storage unit for storing….image” as recited in claim 6;
The specification does not provide sufficient support for structure, material and/or act for the recited storage unit to perform the recited function, the disclosure only nominally mention the term “storage unit” in some places without adequate support for a structure, material and/or act.
2) “an artificial intelligence learning unit for learning….analysis model” as recited in claim 6;
The specification does not discloses sufficient structure, material and act for the recited features as mentioned above to perform the recited functions. The closest mentioning can be found in the instant specification’s [0076] wherein the artificial intelligence learning unit is a machine learning technique such as, PCA analysis, SVM and gradient boosting used with artificial intelligence to perform the learning function such as recited in the claim; however, does not provide sufficient details so that the unit can perform the recited function.
3) “an analysis unit for predicting…model” as recited in claim 6;
The specification does not disclose sufficient support for structure, material or act for the recited feature to perform the recited function. The closet reference can be found at [0074] but merely discloses the mentioning of the unit without giving it a structure, material and/or act to sufficiently understood to perform the recited function.
4) “an image processor for preprocessing….” as recited in claim 7;
The specification does not disclose sufficient support for structure, material or act for the recited feature to perform the recited function.
5) “a mapping unit for feature-mapping….” As recited in claim 10;
The specification does not disclose sufficient support for structure, material or act for the recited feature to perform the recited function. The closet reference can be found at [0020] but merely discloses the mentioning of the unit without giving it a structure, material and/or act to sufficiently understood to perform the recited function.
6) “a classification unit for connecting…..” as recited in claim 10;
The specification does not disclose sufficient support for structure, material or act for the recited feature to perform the recited function. The closet reference can be found at [0020] but merely discloses the mentioning of the unit without giving it a structure, material and/or act to sufficiently understood to perform the recited function.
Because these claim limitations, some are not being interpreted and some are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, 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 these limitations 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 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 6-10 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), claims 6, 7 and 10 have features that are rejected 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. As discussed above in the 112f interpretation section above, the features of the claims, a storage unit for storing….image” as recited in claim 6; “an artificial intelligence learning unit for learning….analysis model” as recited in claim 6; an analysis unit for predicting…model” as recited in claim 6; an image processor for preprocessing….” as recited in claim 7; “a mapping unit for feature-mapping….” As recited in claim 10 and “a classification unit for connecting…..” as recited in claim 10, are lack of written description of support of structure, material and/or act for these recited features to perform the recited functions.
Therefore, the dependent claims depend on these claims 8-9 are also rejected under 112(a) based on dependency.
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 6-10 Claim limitations of , a storage unit for storing….image” as recited in claim 6; “an artificial intelligence learning unit for learning….analysis model” as recited in claim 6; an analysis unit for predicting…model” as recited in claim 6; an image processor for preprocessing….” as recited in claim 7; “a mapping unit for feature-mapping….” As recited in claim 10 and “a classification unit for connecting…..” as recited in claim 10, are lack of written description of support of structure, material and/or act for these recited features to perform the recited functions.. As discussed above in the 112f interpretation section above, the features of the claims, a storage unit for storing….image” as recited in claim 6; “an artificial intelligence learning unit for learning….analysis model” as recited in claim 6; an analysis unit for predicting…model” as recited in claim 6; an image processor for preprocessing….” as recited in claim 7; “a mapping unit for feature-mapping….” As recited in claim 10 and “a classification unit for connecting…..” as recited in claim 10, are lack of written description of support of structure, material and/or act for these recited features to perform the recited 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.
Therefore, the dependent claims depend on these claims 8-9 are also rejected under 112(a) based on dependency.
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.
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 1-10 are rejected under 35 U.S.C. 101
Regarding Independent Claim 1 and its dependent claims 2-5,
Step 1 Analysis: Claim 1 is directed to a process/method, which falls within one of the four statutory categories.
Step 2A Prong 1 Analysis: Claim 1 recites, in part:
“creating an analysis model by learning the spectrum image with artificial intelligence; and
predicting the feature of a test image of an analyte”
The limitations as drafted, are processes that, under broadest reasonable interpretation, covers the performance of the limitation in the mind which falls within the “Mental Processes/Mathematical Concept” grouping of abstract ideas. The limitations of:
“creating an analysis model by learning ….with artificial intelligence” is a mathematical operation series since the creating of a model by learning is a well-known operations of series of math, calculation, computation, applying mathematical concepts in the field of artificial intelligence.
“predicting the feature….an analyte” is a process which a human mind can perform, through process of observation and evaluation such as observing an image and predict the feature of the image according to certain condition/criteria.
Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 Analysis: This judicial exception is not integrated into a practical application. particular, the claim recites the following additional element(s) –
“obtaining a measured spectrum image;
inputting the spectrum image of the sample to the analysis model”
The additional elements of “obtaining an measure spectrum image,” “inputting the spectrum image of the sample” include steps of insignificant extra-solution/post-solution activities of data gathering, data transmitting, etc. [acquiring data/information, transmitting data/info., outputting data/information, displaying data/info., converting data/info., generating data/info., etc.].
The additional element of “the analysis model” includes generic neural network/machine learning model(s)/classifier recited at high level of generality without limiting further, in details, on how the neural network/machine learning model(s) function to arrive at such output, these additional elements are recited as a mere attempt to implement the abstract ideas/judicial exceptions using generic neural network/machine learning models.
Accordingly, 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. The claim as a whole is directed to an abstract idea.. Please see MPEP §2106.04.(d).III.C.
Step 2B Analysis: there are no additional elements, such as for these additional elements as indicated above, that amount to significantly more than the judicial exception. Please see MPEP §2106.05. The claim is directed to an abstract idea.
For all of the foregoing reasons, claim 2-5 does not comply with the requirements of 35 USC 101.
Accordingly, the dependent claims 2-5 do not provide elements that overcome the deficiencies of the independent claim 1. Moreover, claim 2 recites, in part, “preprocessing the spectrum image before creating the analysis model” is an insignificant pre-solution activity of preprocessing data/information. Claim 3 recites, in part, “drawing an axis on the spectrum image” is a step is insignificant extra-solution activity of drawing data/information. Claim 4 recites, in part, “filling or inverting a partial area of the space divided by a spectrum line in the spectrum image” which recites an ”or” indicates a selection, only one of the options is the instant scope of the claim, both options are insignificant extra-solution activities of data/information converting, obtaining, data gathering. Claim 5 recites, in part, “feature-mapping the inputted spectrum image to a convolutional neural network (CNN);” is a step of significant extra-solution activity of data gathering, inputting data into a model, wherein the neural network is recited at high level of generality of a generic neural network additional element; “and connecting the mapped data to a fully connected layer” is insignificant extra-solution activity of data gathering, data connecting to a generic neural network component of a fully connected layer recited at high level of generality additional element.
Accordingly, the dependent claims 2-5 are not patent eligible under 101.
Regarding independent claim 6 and dependent claims 7-10:
Regarding the independent claim 6, the claim recites analogous to the independent claim 1 hence, analyzed under the same approach to be 101 ineligible. Claim 6 further recites additional elements of “an apparatus,” “a storage unit,” and “storing a measured spectrum image” which includes generic well-known computer and computer elements recited at high level of generality, and the additional element of “storing a measure spectrum image” is an insignificant extra-solution activity of data gathering, storing data/information.
The dependent claims 7-10 recite analogous limitations to the previously analyzed claims 2-5 above, hence, are 101 ineligible under the same analysis.
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.
Claims 1-3 and 6-8 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by David L. Perkins et. al. (“US 10,684,388 B2” hereinafter as “Perkins”).
Regarding claim 1, Perkins discloses a method of analyzing a measured spectrum image comprising the steps of (title and abstract): obtaining a measured spectrum image (column 6, last paragraph, discloses obtaining an optical response input of the spectrum response [spectrum image] such as shown in figure 2, moreover column 8, 2nd column, further discloses the input into the neural network includes optical response input such as 300 of figure 3, hence, indicates an obtaining of a measured spectrum image such as 300 of figure 3 and figure 3); creating an analysis model by learning the spectrum image with artificial intelligence (column 9, last 2 paragraphs, train different neural networks [analysis model as claimed] to predict different unknown substances based on the input of the optical response by learning the optical response input of the different substances); and predicting the feature of a test sample of an analyte by inputting the spectrum image of the test sample to the analysis model (column9, last 2 paragraphs, further discloses the neural network model).
Regarding claim 2, Perkins discloses the method according to claim 1, further comprising a step of preprocessing the spectrum image before creating the analysis model (column 13, last par., discloses a quantitative calibration model of the neural network [indicates a calibration of the neural network, or in other words, a pre-processing before using the neural network] which includes performing on the spectrum image of figure 2 and figure 3 such as disclosed in column 13, 2nd par.).
Regarding claim 3, Perkins discloses the method according to claim 2, wherein the step of preprocessing of the spectrum image includes drawing an axis on the spectrum image (the calibration, as discussed above in claim 2, includes drawing the axis on the image such as disclosed in column 13, 2nd par. and column 12, 2nd par.).
Regarding claim 6, Perkins discloses an apparatus for analyzing a measured spectrum comprising: (title and abstract): a storage unit for storing a measured spectrum image (column 6, last paragraph, discloses obtaining an optical response input of the spectrum response [spectrum image] such as shown in figure 2, moreover column 8, 2nd column, further discloses the input into the neural network includes optical response input such as 300 of figure 3, hence, indicates an obtaining of a measured spectrum image such as 300 of figure 3 and figure 3); an artificial intelligence learning unit for learning the spectrum image with artificial intelligence to thereby create an analysis model (column 9, last 2 paragraphs, train different neural networks [analysis model as claimed] to predict different unknown substances based on the input of the optical response by learning the optical response input of the different substances); and an analysis unit for predicting the feature of a test sample of an analyte by inputting the spectrum image of the test sample to the analysis model (column9, last 2 paragraphs, further discloses the neural network model).
Regarding claim 7, Perkins discloses the apparatus according to claim 6, further comprising an image processor for preprocessing the spectrum image before the learning (column 13, last par., discloses a quantitative calibration model of the neural network [indicates a calibration of the neural network, or in other words, a pre-processing before using the neural network] which includes performing on the spectrum image of figure 2 and figure 3 such as disclosed in column 13, 2nd par.).
Regarding claim 8, Perkins discloses the apparatus according to claim 7, wherein the image processing unit draws an axis on the spectrum image (the calibration, as discussed above in claim 7, includes drawing the axis on the image such as disclosed in column 13, 2nd par. and column 12, 2nd par.).
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.
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 4 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over David L. Perkins et. al. (“US 10,684,388 B2” hereinafter as “Perkins”) in view of Joseph W. Boardman et. al. (“An Analysis of Imaging Spectrometer Data Using N-Dimensional Geometry and a Mixture-Tuned Matches Filtering Approach, Nov. 2011, IEEE Transactions on Geoscience and Remote Sensing, Vol. 49, No. 11” hereinafter as ” Boardman”).
Regarding claim 4, Perkins discloses the method according to claim 2 (as discussed above in claim 2).
However, Perkins does not explicitly disclose wherein the step of preprocessing of the spectrum image includes filling or inverting a partial area of the space divided by a spectrum line in the spectrum image.
In the same field of spectrum image processing (title and abstract, Boardman) Boardman discloses wherein the step of preprocessing of the spectrum image includes filling or inverting a partial area of the space divided by a spectrum line in the spectrum image (section III.A, 1st par., discloses preprocessing on the spectrum image, and section III.A, 3rd par., discloses by determining a shift difference based on the row shift difference and the column shift difference of the same band of D [a spectrum line as claimed] to correct the difference by normalizing the noise variance to unity in each band according to equation 4 as disclosed in 6th par., which is analogous to filing a partial area of the space divided by the spectrum line since the shift difference in the band D has a partial area to be even out by normalizing to correct the shift).
Thus, it would have been obvious for a person of ordinary skill in the art before the effective filing date to modify Perkins to perform preprocessing of the spectrum image includes filling or inverting a partial area of the space divided by a spectrum line in the spectrum image as taught by Boardman to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to minimize classification and mapping errors (abstract, Boardman) and perform the spectrum analysis more effectively (section III.A, boardman).
Regarding claim 9, Perkins discloses the apparatus according to claim 7 (as discussed above in claim 7).
However, Perkins does not explicitly disclose wherein the image processing unit fills or inverts a partial area of the space divided by a spectrum line in the spectrum image.
In the same field of spectrum image processing (title and abstract, Boardman) Boardman discloses wherein the image processing unit fills or inverts a partial area of the space divided by a spectrum line in the spectrum image (section III.A, 1st par., discloses preprocessing on the spectrum image, and section III.A, 3rd par., discloses by determining a shift difference based on the row shift difference and the column shift difference of the same band of D [a spectrum line as claimed] to correct the difference by normalizing the noise variance to unity in each band according to equation 4 as disclosed in 6th par., which is analogous to filing a partial area of the space divided by the spectrum line since the shift difference in the band D has a partial area to be even out by normalizing to correct the shift).
Thus, it would have been obvious for a person of ordinary skill in the art before the effective filing date to modify Perkins to perform processing by an image processing unit wherein the image processing unit fills or inverts a partial area of the space divided by a spectrum line in the spectrum image as taught by Boardman to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to minimize classification and mapping errors (abstract, Boardman) and perform the spectrum analysis more effectively (section III.A, boardman).
Claims 5 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over David L. Perkins et. al. (“US 10,684,388 B2” hereinafter as “Perkins”) in view of Vinusha Reddy Kura (“Development and Analysis of Plasmonic Nanomaterials for Biosensors, 2018, University of California, Irvine, Master of Science in Engineering” hereinafter as “Kura”).
Regarding claim 5, Perkins discloses the method of claim 1, wherein the step of creating the analysis model (as discussed above in claim 1).
However, Perkins does not explicitly disclose includes feature-mapping the inputted spectrum image to a convolutional neural network (CNN); and connecting the mapped data to a fully connected layer.
In the same field of spectrum image processing (abstract, Kura) Kura discloses includes feature-mapping the inputted spectrum image to a convolutional neural network (CNN) (section 4.5.2, of page 46, discloses the convolution layer for the analysis model includes ReLU layer to perform feature mapping of a convolutional neural network to process the spectrum image for feature mapping); and connecting the mapped data to a fully connected layer (section 4.5.2, of page 46, discloses the full connection for fully connected layer of neurons in the CNN to connect the mapped data of the ReLU Layer).
Thus, it would have been obvious for a person of ordinary skill in the art before the effective filing date to modify Perkins to perform creating an analysis model includes feature-mapping the inputted spectrum image to a convolutional neural network (CNN) as taught by Kura to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to process the spectrum image and analyze the substance more effectively (abstract, Kura) using the CNN model (section 4.5.2, Kura).
Regarding claim 10, Perkins discloses the method of claim 6, wherein the step of creating the analysis model (as discussed above in claim 6).
However, Perkins does not explicitly disclose wherein the learning unit for creating the analysis model includes a mapping unit for feature-mapping the inputted spectrum image to a convolutional neural network (CNN); and a classification unit for connecting the mapped data to a fully connected layer.
In the same field of spectrum image processing (abstract, Kura) Kura discloses wherein the learning unit for creating the analysis model includes a mapping unit for feature-mapping the inputted spectrum image to a convolutional neural network (CNN) (section 4.5.2, of page 46, discloses the convolution layer for the analysis model includes ReLU layer to perform feature mapping of a convolutional neural network to process the spectrum image for feature mapping); and a classification unit for connecting the mapped data to a fully connected layer (section 4.5.2, of page 46, discloses the full connection for fully connected layer of neurons in the CNN to connect the mapped data of the ReLU Layer).
Thus, it would have been obvious for a person of ordinary skill in the art before the effective filing date to modify Perkins to have a learning unit for creating the analysis model includes a mapping unit for feature-mapping the inputted spectrum image to a convolutional neural network (CNN); and a classification unit for connecting the mapped data to a fully connected layer as taught by Kura to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to process the spectrum image and analyze the substance more effectively (abstract, Kura) using the CNN model (section 4.5.2, Kura).
Pertinent Prior Art(s)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
John L. Robertson et. al. (“US 2021/0215610 A1”) discloses detection of disease specific on using spectrum image processing (abstract) using machine learning neural network ([0086]) based on correcting a baseline oof the spectrum image to obtain baseline corrected image ([0083]) to detect analyte correctly ([00282]).
Conclusion
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/PHUONG HAU CAI/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673