HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES

Ahmet Ornek; Murat Ceylan

doi:10.17780/ksujes.1430479

TR EN

FARKLI ÖLÇEKLERDE ZAYIF DENETİMLİ NESNE TESPİTİ İÇİN HAYCAM VE EIGEN KARŞILAŞTIRILMASI

Abstract

Açıklanabilir Yapay Zeka yaklaşımlarından biri olan Sınıf Aktivasyon haritaları ile bir sınıflama işlemi gerçekleştirildiği zaman, giriş görüntüsü üzerindeki sınıflamaya etki eden alanlar ortaya çıkarılabilmektedir. Yani bir sınıflayıcı modelin görüntünün hangi kısmına bakarak karar verdiği gösterilmektedir. Bu çalışmada açık kaynak bir veri seti olan CUB 200 2011 kullanılarak 200 sınıflı bir sınıflama modeli eğitilmiş ve sınıflama sonuçları EigenCAM ve HayCAM yöntemleri kullanılarak görselleştirilmiştir. Sınıflamaya etki eden alanlar kullanılarak gerçekleştirilen nesne tanıma performansları karşılaştırıldığında EigenCAM yöntemi %30.88 IoU değerine ulaşırken HayCAM yöntemi %41.95 değerine ulaşmaktadır. Elde edilen çıktılar Temel Bileşenler Analizi kullanılarak elde edilen sonuçların (HayCAM), Tekil Değer Ayrışımı kullanılarak elde edilen sonuçlardan (EigenCAM) daha iyi olduğunu göstermektedir.

Keywords

Supporting Institution

Huawei Türkiye Ar-Ge Merkezi

Ethical Statement

Makale, yazarların kendi araştırmalarını ve analizlerini güvenilir ve eksiksiz bir şekilde yansıtmaktadır.

Thanks

Huawei Türkiye Ar-Ge Merkezi

HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES

Abstract

When a classification process is performed using Class Activation Maps, which is one of the Explainable Artificial Intelligence approaches, the areas influencing the classification on the input image can be revealed. In other words, it is demonstrated which part of the image the classifier model looks at to make a decision. In this study, a 200-class classification model was trained using the open-source dataset CUB 200 2011, and the classification results were visualized using the EigenCAM and HayCAM methods. When comparing object detection performances based on the areas influencing classification, the EigenCAM method reaches an IoU (Intersection over Union) value of 30.88%, while the HayCAM method reaches a value of 41.95%. The obtained results indicate that outputs derived using Principal Component Analysis (HayCAM) are better than those obtained using Singular Value Decomposition (EigenCAM).

Keywords

Supporting Institution

Huawei Türkiye R&D Center

Ethical Statement

The paper reflects the authors' own research and analysis in a truthful and complete manner.

Thanks

Huawei Türkiye R&D Center

References

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Details

Primary Language

English

Subjects

Computer Vision, Image Processing, Deep Learning

Journal Section

Research Article

Authors

Ahmet Ornek ^*
0000-0001-7254-9316
Türkiye

Murat Ceylan
0000-0001-6503-9668
Türkiye

Publication Date

September 3, 2024

Submission Date

February 2, 2024

Acceptance Date

July 22, 2024

Published in Issue

Year 2024 Volume: 27 Number: 3

DOI

https://doi.org/10.17780/ksujes.1430479

IZ

https://izlik.org/JA78LA67FG

Cite

RIS / Bibtex

APA

Ornek, A., & Ceylan, M. (2024). HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 27(3), 1078-1088. https://doi.org/10.17780/ksujes.1430479

AMA

1.Ornek A, Ceylan M. HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES. KSU J. Eng. Sci. 2024;27(3):1078-1088. doi:10.17780/ksujes.1430479

Chicago

Ornek, Ahmet, and Murat Ceylan. 2024. “HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES”. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 27 (3): 1078-88. https://doi.org/10.17780/ksujes.1430479.

EndNote

Ornek A, Ceylan M (September 1, 2024) HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 27 3 1078–1088.

IEEE

[1]A. Ornek and M. Ceylan, “HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES”, KSU J. Eng. Sci., vol. 27, no. 3, pp. 1078–1088, Sept. 2024, doi: 10.17780/ksujes.1430479.

ISNAD

Ornek, Ahmet - Ceylan, Murat. “HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES”. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi 27/3 (September 1, 2024): 1078-1088. https://doi.org/10.17780/ksujes.1430479.

JAMA

1.Ornek A, Ceylan M. HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES. KSU J. Eng. Sci. 2024;27:1078–1088.

MLA

Ornek, Ahmet, and Murat Ceylan. “HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES”. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, vol. 27, no. 3, Sept. 2024, pp. 1078-8, doi:10.17780/ksujes.1430479.

Vancouver

1.Ahmet Ornek, Murat Ceylan. HAYCAM VS EIGENCAM FOR WEAKLY-SUPERVISED OBJECT DETECTION ACROSS VARYING SCALES. KSU J. Eng. Sci. 2024 Sep. 1;27(3):1078-8. doi:10.17780/ksujes.1430479

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Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

https://doi.org/10.17780/ksujes.1735791