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Main Authors: Coutinho, Catarina P., Merhab, Aneeqa, Petkovic, Janko, Zanchetta, Ferdinando, Fioresi, Rita
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2504.17619
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author Coutinho, Catarina P.
Merhab, Aneeqa
Petkovic, Janko
Zanchetta, Ferdinando
Fioresi, Rita
author_facet Coutinho, Catarina P.
Merhab, Aneeqa
Petkovic, Janko
Zanchetta, Ferdinando
Fioresi, Rita
contents We exploit the mathematical modeling of the visual cortex mechanism for border completion to define custom filters for CNNs. We see a consistent improvement in performance, particularly in accuracy, when our modified LeNet 5 is tested with occluded MNIST images.
format Preprint
id arxiv_https___arxiv_org_abs_2504_17619
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Enhancing CNNs robustness to occlusions with bioinspired filters for border completion
Coutinho, Catarina P.
Merhab, Aneeqa
Petkovic, Janko
Zanchetta, Ferdinando
Fioresi, Rita
Computer Vision and Pattern Recognition
Artificial Intelligence
We exploit the mathematical modeling of the visual cortex mechanism for border completion to define custom filters for CNNs. We see a consistent improvement in performance, particularly in accuracy, when our modified LeNet 5 is tested with occluded MNIST images.
title Enhancing CNNs robustness to occlusions with bioinspired filters for border completion
topic Computer Vision and Pattern Recognition
Artificial Intelligence
url https://arxiv.org/abs/2504.17619