DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to communications: RCE filed on 8/1/2025.
Claims 1-20 are pending. Claims 1, 10, and 15 are independent.
The previous rejection of claims 1-20 under 35 USC § 103 have been withdrawn in view of the amendment.
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: “means for receiving input”, “means for modelling”, “means for generating”, “means for determining”, “means for computing”, “means for generating”, “means for transmitting”, “means for annotating” and “means for training” in claim 10-14.
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 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 10-14 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 enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
Claims 10-14 recite:
“means for modelling 1) an in-domain feature space of the AI based system based on the projection matrix and 2) an out-of-domain feature space of the AI based system based on a transpose of the projection matrix,” “means for generating probability functions,” and “means for determining whether the input data is out-of-domain” in claim 10.
“means for computing the in-domain feature space,” “means for computing one or more orthogonal linear projection matrices,” and “means for computing the out-of-domain feature space” in claim 11.
“means for generating the probability distribution functions” in claim 12.
“means for transmitting a notification” in claim 13.
Specification discloses a module for modeling, generating, and determining (Spec para[0006]). However the specification doesn’t sufficiently disclose an algorithm performed by each of the means to perform the claimed functions. Pursuant MPEP § 2161.01, “original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved”. However nothing in claim 10 of the instant Specification “provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention”. A person of ordinary skill in the art wouldn’t know how each module are able to accomplish the claimed functions, such as modeling, generating, and determining. As Such, claims 10-14 lack written description, because the instant specification doesn’t sufficiently describe an algorithm describing how each of the modules can perform the claimed function.
Dependent claims 11-14 are rejected as they depend on the claims above.
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 10-14 recite:
“means for modelling 1) an in-domain feature space of the AI based system based on the projection matrix and 2) an out-of-domain feature space of the AI based system based on a transpose of the projection matrix,” “means for generating probability functions,” and “means for determining whether the input data is out-of-domain” in claim 10.
“means for computing the in-domain feature space,” “means for computing one or more orthogonal linear projection matrices,” and “means for computing the out-of-domain feature space” in claim 11.
“means for generating the probability distribution functions” in claim 12.
“means for transmitting a notification” in claim 13.
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. Specification discloses a module for modeling, generating, and determining (Spec para[0006]), but does not disclose specific structure 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.
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.
Claim(s) 1-2, 5-7, 10-11, and 14-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mohseni et al. (US2021/0142160) in view of Zhang ‘968 (US2020/0073968).
In regards to claim 1, Mohseni et al. discloses a method comprising:
receiving input data for inputting into an AI (artificial intelligence) based system, (Mohseni et al. fig. 5 502 para[0070], at block 502 receives input data);
generating probability distribution functions, in the in-domain feature space and the out-of-domain feature space, for the input data and for the data that the AI based system is trained to classify (Mohseni et al. fig. 5 506para[0070], uses softmax function to generate probability distribution); and
determining whether the input data is out-of-domain of the AI based system based on the probability distribution functions for the input data and for the data that the AI based system is trained to classify (Mohseni et al. fig. 5 510 para[0071], determines if input data is out-of-distribution using values of softmax probability distribution).
Mohseni further discloses modeling and in-domain feature space of the AI based system and an out-of-domain feature space of the AI based system, the in-domain feature space corresponding to features of data that the AI based system is trained to classify and the out-of-domain feature space corresponding to features of data that the AI based system is not trained to classify (Mohseni et al. fig. 5 504 para[0070], generating values at a first set of output nodes, and second set of output nodes, based on received input data, and generating softmax values corresponding to output nodes to determine if input was out-of-distribution or not).
Mohseni et al. does not explicitly disclose the AI based system comprising a machine learning based network comprising one or more projection layers implemented with a projection matrix;
Modeling 1) an in-domain feature space based on the projection matrix and 2) and out of domain feature space based on the transpose of the feature space.
However Zhang ‘968 discloses the AI based system comprising a machine learning based network comprising one or more projection layers implemented with a projection matrix (Zhang ‘968 para[0043], the attention model can be configured to identify the core regions of the sketches and synthetic sketches during the learning process. The attention model can include a convolutional layer and a softmax function with a threshold can be applied to the output for obtaining a binary attention mask);
modelling 1) an in-domain feature space of the AI based system based on the projection matrix and 2) an out-of-domain feature space of the AI based system based on a transpose of the projection matrix, the in-domain feature space corresponding to features of data that the AI based system is trained to classify and the out-of-domain feature space corresponding to features of data that the AI based system is not trained to classify (Zhang ‘968 para[0110]-[0120], models feature space based on projection matrix D and transposed matrix of D).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to have combined the out of distribution detection of Mohseni et al. with the domain migration method of Zhang ‘968 in order to preserve semantic consistency between domains (Zhang ‘968 para[0010]).
In regards to claim 2, Mohseni et al. as modified by Zhang ‘968 discloses the method of claim 1, wherein modelling an in-domain feature space of the AI based system and an out-of-domain feature space of the AI based system comprises:
computing the in-domain feature space based on the projection matrix (Zhang ‘968 para[0042], identifies in-domain feature space of image and sketch domains);
computing one or more orthogonal linear projection matrices for the out-of-domain feature space based on the transpose of the projection matrix (Zhang ‘968 para [0054], uses discriminator to identify out of domain space); and
computing the out-of-domain feature space based on the one or more orthogonal linear projection matrices for the out-of-domain feature space (Zhang ‘968 para[0062], computes out of domain feature space based on generator and discriminator).
In regards to claim 5, Mohseni et al. as modified by Zhang et al. discloses the method of claim 1, further comprising:
in response to determining that the input data is out-of-domain of the AI based system:
annotating the input data (Mohseni et al. para[0060], assigns pseudo-labels with values of 100 or greater for OOD inputs); and
training the AI based system based on the annotated input data (Mohseni et al. para[0060], pseudo labeled samples used to train neural network).
In regards to claim 6, Mohseni et al. as modified by Zhang et al. discloses the method of claim 1, further comprising:
in response to determining that the input data is not out-of-domain of the AI based system, generating a prediction from the input data by the AI based system (Mohseni et al. para[0106], infer or predict information based on input).
In regards to claim 7, Mohseni et al. as modified by Zhang et al. discloses the method of claim 1, wherein the receiving, the modelling, the generating, and the determining are performed by a module combined with the AI based system and the module combined with the AI based system generates a prediction from the input data and the determination of whether the input data is out-of-domain of the AI based system (Mohseni et al. para[0109], infers OOD input data)
Claim 10-11 and 14 recite substantially similar limitations to claims 1-2 and 7. Thus claims 10-11 and 14 are rejected along the same rationale as claims 1-2 and 7.
Claims 15-16 and 17-18 recite substantially similar limitations to claims 1-2, and 5-6. Thus claims 15-16 and 17-18 are rejected along the same rationale as claims 1-2, and 5-6.
Claim(s) 3-4, 8-9, 12-13, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mohseni et al. in view of Zhang ‘968 and Mohseni ‘597 (US2022/0318557).
In regards to claim 3, Mohseni et al. as modified by Zhang ‘968 discloses the method of claim 1. Mohseni et al. does not explicitly disclose wherein generating probability distribution functions, in the in-domain feature space and the out-of-domain feature space, for the input data and for the data that the AI based system is trained to classify comprises:
generating the probability distribution functions using a Gaussian process model or a combination of Gaussian probability distribution models fitted to available data.
However Mohseni ‘557 discloses wherein generating probability distribution functions, in the in-domain feature space and the out-of-domain feature space, for the input data and for the data that the AI based system is trained to classify comprises:
generating the probability distribution functions using a Gaussian process model or a combination of Gaussian probability distribution models fitted to available data (Mohseni ‘557 para[0058], transforms input data using Gaussian process).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to have combined the out of distribution detection of Mohseni et al. with the out-of-distribution identification method of Mohseni ‘557 in order to identify and prevent classification errors (Mohseni ‘557 para[0002]).
In regards to claim 4, Mohseni et al. as modified by Zhang ‘968 discloses the method of claim 1. Mohseni et al. does not explicitly disclose further comprising:
in response to determining that the input data is out-of-domain of the AI based system, transmitting a notification to a user for reviewing a prediction generated by the AI based system from the input data.
However Mohseni ‘557 discloses further comprising:
in response to determining that the input data is out-of-domain of the AI based system, transmitting a notification to a user for reviewing a prediction generated by the AI based system from the input data (Mohseni ‘557 fig. 6 para[0088], generates OOD notification if OOD data is detected at block 606).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to have combined the out of distribution detection of Mohseni et al. with the out-of-distribution identification method of Mohseni ‘557 in order to identify and prevent classification errors (Mohseni ‘557 para[0002]).
In regards to claim 8, Mohseni et al. as modified by Zhang ‘968 discloses the method of claim 1. Mohseni et al. does not explicitly disclose further comprising:
selecting one of a plurality of algorithms of the AI based system based on the determining.
However Mohseni ‘557 discloses further comprising:
selecting one of a plurality of algorithms of the AI based system based on the determining (Mohseni ‘557 para[0199], selects from a variety of vision algorithms for object detection).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to have combined the out of distribution detection of Mohseni et al. with the out-of-distribution identification method of Mohseni ‘557 in order to identify and prevent classification errors (Mohseni ‘557 para[0002]).
In regards to claim 9, Mohseni et al. as modified by Zhang ‘968 discloses the method of claim 1. Mohseni et al. does not explicitly disclose wherein the AI based system is for medical imaging analysis.
However Mohseni ‘557 discloses wherein the AI based system is for medical imaging analysis (Mohseni ‘557 para[0078], domain of application includes analysis of medical imagery such as X-ray imagery).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to have combined the out of distribution detection of Mohseni et al. with the out-of-distribution identification method of Mohseni ‘557 in order to identify and prevent classification errors (Mohseni ‘557 para[0002]).
Claims 12-13 recite substantially similar limitation to claims 3-4. Thus claims 12-13 are rejected along the same rationale as claims 3-4.
Claims 19-20 recite substantially similar limitations to claims 8-9. Thus claims 19-20 are rejected along the same rationale as claims 8-9.
Response to Arguments
Applicant’s arguments with respect to claims 1-20 have been considered but are moot because the arguments do not apply the current rejection.
Conclusion
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/N.H/Examiner, Art Unit 2141
/MATTHEW ELL/Supervisory Patent Examiner, Art Unit 2141