Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks

Fuente: arXiv
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Auteurs principaux: Zhang, Yuyan, Soydaner, Derya, Behrad, Fatemeh, Koßmann, Lisa, Wagemans, Johan
Format: Preprint
Publié: 2024
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author Zhang, Yuyan
Soydaner, Derya
Behrad, Fatemeh
Koßmann, Lisa
Wagemans, Johan
author_facet Zhang, Yuyan
Soydaner, Derya
Behrad, Fatemeh
Koßmann, Lisa
Wagemans, Johan
contents Deep neural networks perform well in object recognition, but do they perceive objects like humans? This study investigates the Gestalt principle of closure in convolutional neural networks. We propose a protocol to identify closure and conduct experiments using simple visual stimuli with progressively removed edge sections. We evaluate well-known networks on their ability to classify incomplete polygons. Our findings reveal a performance degradation as the edge removal percentage increases, indicating that current models heavily rely on complete edge information for accurate classification. The data used in our study is available on Github.
format Preprint
id arxiv_https___arxiv_org_abs_2411_00627
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks
Zhang, Yuyan
Soydaner, Derya
Behrad, Fatemeh
Koßmann, Lisa
Wagemans, Johan
Computer Vision and Pattern Recognition
Machine Learning
Deep neural networks perform well in object recognition, but do they perceive objects like humans? This study investigates the Gestalt principle of closure in convolutional neural networks. We propose a protocol to identify closure and conduct experiments using simple visual stimuli with progressively removed edge sections. We evaluate well-known networks on their ability to classify incomplete polygons. Our findings reveal a performance degradation as the edge removal percentage increases, indicating that current models heavily rely on complete edge information for accurate classification. The data used in our study is available on Github.
title Investigating the Gestalt Principle of Closure in Deep Convolutional Neural Networks
topic Computer Vision and Pattern Recognition
Machine Learning
url https://arxiv.org/abs/2411.00627