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Knowledge guided deep learning for general-purpose computer vision applications

Djenouri, Youcef; Belbachir, Ahmed Nabil; Jhaveri, Rutvij H.; Djenouri, Djamel

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Authors

Youcef Djenouri

Ahmed Nabil Belbachir

Rutvij H. Jhaveri



Abstract

This research targets general-purpose smart computer vision that eliminates reliance on domain-specific knowledge to reach adaptable generic models for flexible applications. It proposes a novel approach in which several deep learning models are trained for each image. Statistical information of each trained image is then calculated and stored with the loss values of each model used in the training phase. The stored information is finally used to select the appropriate model for each new image data in the testing phase. To efficiently select the appropriate model, a kNN (k Nearest Neighbors) strategy is used to select the best model in the testing phase. The developed framework called KGDL (Knowledge Guided Deep Learning) was evaluated and tested using two computer vision benchmarks, 1) ImageNet for image classification, and 2) COCO for object detection. The results reveal the effectiveness of KGDL in terms of accuracy and competitiveness of inference runtime. In particular, it achieved 94 % of classification rate in ImageNet, and 92% of intersection over union in COCO dataset.

Presentation Conference Type Conference Paper (published)
Conference Name International Conference on Computer Analysis of Images and Patterns
Acceptance Date Aug 1, 2023
Online Publication Date Sep 20, 2023
Publication Date Sep 20, 2023
Deposit Date Oct 5, 2023
Publicly Available Date Sep 21, 2024
Publisher Springer Verlag
Volume 14184 LNCS
Pages 185-194
Book Title Computer Analysis of Images and Patterns
ISBN 9783031442360
DOI https://doi.org/10.1007/978-3-031-44237-7_18
Public URL https://uwe-repository.worktribe.com/output/11152187
Additional Information First Online: 20 September 2023; Conference Acronym: CAIP; Conference Name: International Conference on Computer Analysis of Images and Patterns; Conference City: Limassol; Conference Country: Cyprus; Conference Year: 2023; Conference Start Date: 25 September 2023; Conference End Date: 28 September 2023; Conference Number: 20; Conference ID: caip2023; Conference URL: https://cyprusconferences.org/caip2023/; Type: Single-blind; Conference Management System: https://www.easyacademia.org; Number of Submissions Sent for Review: 67; Number of Full Papers Accepted: 54; Number of Short Papers Accepted: 0; Acceptance Rate of Full Papers: 81% - The value is computed by the equation "Number of Full Papers Accepted / Number of Submissions Sent for Review * 100" and then rounded to a whole number.; Average Number of Reviews per Paper: 2.06; Average Number of Papers per Reviewer: 2.09; External Reviewers Involved: No

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Copyright Statement
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-44237-7_18.





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