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 required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 4 January 2025 is being considered by the examiner.
It is noted that the CN 109200142 A reference referred to in paragraph [0006] of the specification is not listed on the information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." The reference is being considered and cited by the examiner on form PTO-892.
Claim Objections
Claims 1 and 7 are objected to because of the following informalities:
Claim 1 has two periods. One at the end of the limitation starting “S43: merging…evaluation of accuracy performance indexes.” Then again in the last limitation reciting “S05…for image recognition.” Thus, the period in the “S43” limitation should be changed to a comma.
Further, claim 1 should make use of indentations for the sub-steps located within step S04 in order to make the readability of the claim easier to follow and add proper coordinating conjunction to connect the clauses [add “and”]. For example:
1. An image recognition method based on multi-population alternate evolution neural architecture search, comprising the following steps:
S01: acquiring image data and determining a search network according to a target task;
S02: constructing a supernet and pre-training the supernet according to preset parameters;
S03: dividing a network structure search space into multiple sub-spaces through an L-layer structure of a neural network, and randomly selecting N candidate sub-networks from the sub-spaces to form an initialized population;
SO4: sampling multiple populations from the multiple sub-spaces for alternate evolution, and selecting frontier individuals from a merged population in a multi-objective environment to generate a next parent population for multi-population alternate evolution, wherein the multi-population alternate evolution comprises:
S41: generating a current offspring population Ql according to preset crossover and mutation parameters as well as offspring generation strategies;
S42: migrating excellent individuals from other populations to a current evolution population to obtain a migrated population Ml, wherein a method for obtaining a migrated population Ml, comprises:
maintaining migration archives and selecting excellent individuals from a contemporary population into a migration archive set according to a multi-objective evolutionary algorithm;
determining the number of migrated individuals according to an adjacent distance of each population; and
selecting the migrated individuals of the population according to a degree of similarity between the individuals and the populations; and
S43: merging the parent population Pl, the offspring population Ql, and the migrated population Ml to form a merged population, decoding the individuals within the merged population into corresponding sub-network structures si and inheriting weights Ws(si) from the supernet S, and then conducting fine-tuning training on a training dataset followed by an evaluation of accuracy performance indexes, and
S05: obtaining an optimal neural network model for image recognition.
Similarly for claim 7:
7. An image recognition system based on multi-population alternate evolution neural architecture search, comprising:
an image acquisition module, configured to acquire image data and determine a search network according to a target task;
a supernet construction and training module, configured to construct a supernet and pre-train the supernet according to preset parameters;
an initialization module, configured to divide a network structure search space into multiple sub-spaces through an L-layer structure of a neural network, and randomly select N candidate sub-networks from the sub-spaces to form an initialized population;
a multi-population alternate evolution module, configured to sample multiple populations from the multiple sub-spaces for alternate evolution, and select frontier individuals from a merged population in a multi-objective environment to generate a next parent population for multi-population alternate evolution, wherein the multi-population alternate evolution comprises:
S41: generating a current offspring population Ql according to preset crossover and mutation parameters as well as offspring generation strategies;
S42: migrating excellent individuals from other populations to a current evolution population to obtain a migrated population Ml, wherein a method for obtaining a migrated population Ml comprises:
maintaining migration archives and selecting excellent individuals from a contemporary population into a migration archive set according to a multi-objective evolutionary algorithm;
determining the number of migrated individuals according to an adjacent distance of each population; and
selecting the migrated individuals of the population according to a degree of similarity between individuals and populations; and
S43: merging the parent population Pl, the offspring population Ql, and the migrated population Ml to form a merged population, decoding the individuals within the merged population into corresponding sub-network structures si and inheriting weights Ws(si) from the supernet S, and then conducting fine-tuning training on a training dataset followed by an evaluation of accuracy performance indexes; and
an image recognition module, configured to obtain an optimal neural network model for image recognition.
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 limitation(s) is/are:
“an image acquisition module, configured to…” in claim 7;
“a supernet construction and training module, configured to…” in claim 7;
“an initialization module, configured to…” in claim 7;
“a multi-population alternate evolution module, configured to…” in claim 7; and
“an image recognition module, configured to…” in claim 7.
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. However, there isn’t any corresponding structure described in the specification as performing the claimed function. Figure 2 is merely a block diagram and there is no description regarding any specific structure for the claimed module.
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 7 and 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 “an image acquisition module, configured to…”, “a supernet construction and training module, configured to…”, “an initialization module, configured to…”, “a multi-population alternate evolution module, configured to…”, and “an image recognition module, configured to…” in claim 7 invoke 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. The disclosure is devoid of any structure that performs the function in the claim. Figure 2 merely shows a block diagram, and there isn’t any corresponding structure described in the specification as performing the claimed function. 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.
With regards to claim 8, the claim recites the limitation “the image recognition method.” There is insufficient antecedent basis for this limitation in the claim.
For examination purposes, the examiner will assume that claim 8 should recite “the image recognition method of claim 1…” The claim should be amended as such.
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.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 8 recites “A computer storage medium.” The broadest reasonable interpretation of a claim drawn to a computer readable medium (also called machine readable medium and other such variations) typically covers forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer readable media, particularly when the specification is silent. See MPEP 2111.01.
The USPTO recognizes that applicants may have claims directed to computer readable media that cover signals per se, which the USPTO must reject under 35 U.S.C. § 101 as covering both non-statutory subject matter and statutory subject matter. In an effort to assist the patent community in overcoming a rejection or potential rejection under 35 U.S.C. § 101 in this situation, the USPTO suggests the following approach. A claim drawn to such a computer readable medium that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments to avoid a rejection under 35 U.S.C. § I01 by adding the limitation "non-transitory" to the claim. Cf. Animals -Patentability, 1 077 0ff. Gaz. Pat. Office 24 (April 21, 1987) (suggesting that applicants add the limitation "non-human" to a claim covering a multi-cellular organism to avoid a rejection under 35 U.S.C. § 101). Such an amendment would typically not raise the issue of new matter, even when the specification is silent because the broadest reasonable interpretation relies on the ordinary and customary meaning that includes signals per se. The limited situations in which such an amendment could raise issues of new matter occur, for example, when the specification does not support a non-transitory embodiment because a signal per se is the only viable embodiment such that the amended claim is impermissibly broadened beyond the supporting disclosure. See, e.g., Gentry Gallery, Inc. v. Berkline Corp., 134 F.3d 1473 (Fed. Cir. 1998).
Allowable Subject Matter
Claims 1-6 are allowed.
Claims 7-8 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
In the closest prior art:
Lu et al. (CN 109299142 A) discloses a method for searching a convolutional neural network structure based on an evolutionary algorithm. The method includes setting an initial population, then using a queue to produce untrained chromosomes, eventually training and calculating the fitness, and outputting the best model.
Zhang et al. (CN 117252238 A) disclose an image classification neural network architecture search system comprising: (i) obtaining sample data; (ii) initializing the population; (iii) propagating which comprises randomly selecting the parent structure in the original population to propagate to obtain the sub-structure set, and combining the sub-structure set with the original population to form a new population.; (iv) calculating zero cost index; (v) selecting the framework; and (vi) outputting the final framework, where according to the network architecture selected in the step v, repeating the steps iii-v, finally selecting the network architecture with the highest zero cost index as the final output network architecture.
Li et al. (CN 116739765 A) disclose of using NAS, and discloses generally of an evolution method used shown in Figure 10.
Piergiovanni et al. (US 2022/0366257) disclose of using NAS, and give a specific example of an evolutionary search approach in Figure 1A and described in paragraphs [0042]-[0043] and [0049]-[0055].
E. Real, A. Aggarwal, Y. Huang, and Q. V. Le (Regularized evolution for image classifier architecture search) disclose an evolutionary algorithm for NAS (see Algorithm 1). Specifically, at each cycle, the algorithm samples S random models from the population, each drawn uniformly at random with replacement. The model with the highest validation fitness within this sample is selected as the parent. A new architecture, called the child, is constructed from the parent by the application of a transformation called a mutation. A mutation causes a simple and random modification of the architecture and is described in detail below. Once the child architecture is constructed, it is then trained, evaluated, and added to the population. Further, in this paper, a novel approach is applied: killing the oldest model in the population—that is, removing from the population the model that was trained the earliest (“remove dead from left of pop” in Algorithm 1). This favors the newer models in the population. This is referred to as aging evolution. In the context of architecture search, aging evolution allows more exploration of the search space, instead of zooming in on good models too early, as non-aging evolution would.
P. Yotchon and Y. Jewajinda (Hybrid Multi-population Evolution based on Genetic Algorithm and Regularized Evolution for Neural Architecture Search) disclose of multi-population evolution for NAS. See Figure 5, which shows the algorithm. In the migration policy, the best individual in each subpopulation is exchanged between neighboring subpopulation and replace a randomly selected individual in the destination subpopulation as shown in Fig. 3 and 4.
However, none of the closest prior art, even in combination, discloses the specifically claimed multi-population alternate evolution steps: “S41: generating a current offspring population Ql according to preset crossover and mutation parameters as well as offspring generation strategies; S42: migrating excellent individuals from other populations to a current evolution population to obtain a migrated population Ml, wherein a method for obtaining a migrated population Ml, comprises: maintaining migration archives and selecting excellent individuals from a contemporary population into a migration archive set according to a multi-objective evolutionary algorithm; determining the number of migrated individuals according to an adjacent distance of each population; and selecting the migrated individuals of the population according to a degree of similarity between the individuals and the populations; and S43: merging the parent population Pl, the offspring population Ql, and the migrated population Ml to form a merged population, decoding the individuals within the merged population into corresponding sub-network structures si and inheriting weights Ws(si) from the supernet S…”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
J. Zou, H. Chu, Y. Xia, J. Xu, Y. Liu, Z. Hou ("Multiple Population Alternate Evolution Neural Architecture Search") discloses the claimed invention. Since the foreign priority application has not been translated, the effective filing date of the application for examination is 4 January 2025. However, since the publication date of the NPL is 11 March 2024, and the publication has listed inventors in common with the present application, the NPL is disqualified as prior art under the exceptions of 102(b)(1)(A). See MPEP § 717.01 III.A, which recites:
SITUATIONS WHERE 37 CFR 1.130(a) AFFIDAVITS OR DECLARATIONS ARE NOT REQUIRED (A) A declaration under 37 CFR 1.130(a) is not required when a public disclosure, subject to the exceptions of 35 U.S.C. 102(b)(1)(A), is by one or more joint inventor(s) or the entire inventive entity of the application under examination and does not name anyone else. For example, if an application names A, B, and C as the inventive entity, a journal publication names as authors A and B, and the publication date is one year or less before the effective filing date of the claimed invention, then the publication should not be applied in a prior art rejection because it is apparent that the disclosure is a grace period disclosure.
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/STEPHEN G SHERMAN/Primary Examiner, Art Unit 2621
7 August 2026
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