Prosecution Insights
Last updated: October 02, 2026
Application No. 18/419,849

IMAGE RETRIEVING DEVICE AND IMAGE RETRIEVING METHOD

Final Rejection §112
Filed
Jan 23, 2024
Priority
Aug 26, 2021 — continuation of PCTJP2021031270
Examiner
SORRIN, AARON JOSEPH
Art Unit
2672
Tech Center
2600 — Communications
Assignee
Mitsubishi Electric Corporation
OA Round
2 (Final)
76%
Grant Probability
Favorable
3-4
OA Rounds
4m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allowance Rate
57 granted / 75 resolved
+14.0% vs TC avg
Strong +42% interview lift
Without
With
+42.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
32 currently pending
Career history
102
Total Applications
across all art units

Statute-Specific Performance

§101
20.0%
-20.0% vs TC avg
§103
37.1%
-2.9% vs TC avg
§102
14.1%
-25.9% vs TC avg
§112
28.0%
-12.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 75 resolved cases

Office Action

§112
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Arguments The IDS with proper indication of consideration is now provided. All prior objections and rejections are withdrawn. However, the amendments have created several new issues under 35 USC 112(b), explained below. 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 and 3-5 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. Claims 1 and 3-5 recite the limitation "a possibility”. There is improper antecedent basis for this limitation in the claim. The first instance is being interpreted as written, and each subsequent instance is being interpreted as “the possibility”. Claim 3 recites various antecedence issues that have been created due to the amendment of claim 1 including “learning images”, “a plurality of images”, “learning of the reliability”, and “teacher data”. These are being interpreted as referencing the identically claimed elements of claim 1. Claims 3 and 4 each describe a method in which “learning of the reliability is performed”. Amended claim 1 however now describes a method in which “learning of the reliability is performed”. This has created an issue of indefiniteness wherein it has become unclear if these methods are used in parallel, sequentially, or as alternatives to each other. It appears that they are alternative learning methods, and are being interpreted accordingly. Claim 4 recites “learning images”, and “learning of the reliability”, which have improper antecedence. These are being interpreted as referencing the identically claimed elements of claim 1. Allowable Subject Matter Claims 1 and 3-5 are rejected under 35 USC 112(b) but would be allowable if amended to overcome 35 USC 112(b) rejections. The following is a statement of reasons for the indication of allowable subject matter: With respect to claims 1 and 5 (as well as dependent claims 3-4), in addition to other limitations in the claims the Prior Art of Record fails to teach, disclose or render obvious the applicant' s invention as claimed, in particular: Claim 1 (and similarly claim 5) recites: “An image retrieving device comprising: processing circuitry configured to give a query image that is an image to be identified to a first learning model, acquire a feature vector of the query image from the first learning model, give each of a plurality of gallery images that are images to be identified to the first learning model, and acquire a feature vector of each of the gallery images from the first learning model; give the query image to a second learning model, and acquire, from the second learning model, reliability of retrieval when K (K is an integer equal to or more than one) gallery images having a possibility of including a subject included in the query image are retrieved from the plurality of the gallery images, wherein the K gallery images from the plurality of the gallery images are retrieved on a basis of the feature vector of the acquired query image and the feature vector of each of the gallery images; and specify the reliability of retrieval from the acquired reliability, wherein the second learning model is a learning model in which each of learning images that are a plurality of images for learning included in a learning image group is sequentially given as a reference image, and learning of the reliability is performed when the reliability of retrieval at a time when K learning images having a possibility of including a subject included in the reference image are retrieved from among learning images other than the reference image included in the learning image group is given as teacher data.” Doumbouya teaches matching of a query image to gallery images based on matching feature vectors extracted from the images. Li teaches a method of analyzing the difficulty of a particular image query search based on the search results and a trained model. Tian discloses strategies for assessing the quality of retrieved search results in response to a query based on a preference learning model. Geng teaches a ranking strategy for image search results in which both textual and visual features are used in the ranking. Alcock teaches a method for improving speed of similarity searches that includes calculating a Euclidian distance between feature vectors of a query image and images of a database. Dhua teaches a method for identifying visual similarities that includes extracting and comparing feature vectors of query images and images in a dataset, wherein confidence scores are generated that indicate match likelihood. However, none of these references disclose the bolded limitations above. The closest reference is Li, which discloses the ‘second machine learning model’. However, the model training of Li is expressly described as differing significantly from the training method implemented in the bolded limitation. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to AARON JOSEPH SORRIN whose telephone number is (703)756-1565. The examiner can normally be reached Monday - Friday 9am - 5pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sumati Lefkowitz can be reached at (571) 272-3638. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /AARON JOSEPH SORRIN/Examiner, Art Unit 2672 /SUMATI LEFKOWITZ/Supervisory Patent Examiner, Art Unit 2672
Read full office action

Prosecution Timeline

Jan 23, 2024
Application Filed
Jan 13, 2026
Non-Final Rejection mailed — §112
Apr 10, 2026
Applicant Interview (Telephonic)
Apr 10, 2026
Examiner Interview Summary
May 12, 2026
Response Filed
Jun 09, 2026
Final Rejection mailed — §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
76%
Grant Probability
99%
With Interview (+42.0%)
3y 0m (~4m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 75 resolved cases by this examiner. Grant probability derived from career allowance rate.

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