LE-CapsNet: A Light and Enhanced Capsule Network

Fuente: arXiv
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Main Authors: Shiri, Pouya, Baniasadi, Amirali
Format: Preprint
Published: 2025
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author Shiri, Pouya
Baniasadi, Amirali
author_facet Shiri, Pouya
Baniasadi, Amirali
contents Capsule Network (CapsNet) classifier has several advantages over CNNs, including better detection of images containing overlapping categories and higher accuracy on transformed images. Despite the advantages, CapsNet is slow due to its different structure. In addition, CapsNet is resource-hungry, includes many parameters and lags in accuracy compared to CNNs. In this work, we propose LE-CapsNet as a light, enhanced and more accurate variant of CapsNet. Using 3.8M weights, LECapsNet obtains 76.73% accuracy on the CIFAR-10 dataset while performing inference 4x faster than CapsNet. In addition, our proposed network is more robust at detecting images with affine transformations compared to CapsNet. We achieve 94.3% accuracy on the AffNIST dataset (compared to CapsNet 90.52%).
format Preprint
id arxiv_https___arxiv_org_abs_2511_11708
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LE-CapsNet: A Light and Enhanced Capsule Network
Shiri, Pouya
Baniasadi, Amirali
Computer Vision and Pattern Recognition
Capsule Network (CapsNet) classifier has several advantages over CNNs, including better detection of images containing overlapping categories and higher accuracy on transformed images. Despite the advantages, CapsNet is slow due to its different structure. In addition, CapsNet is resource-hungry, includes many parameters and lags in accuracy compared to CNNs. In this work, we propose LE-CapsNet as a light, enhanced and more accurate variant of CapsNet. Using 3.8M weights, LECapsNet obtains 76.73% accuracy on the CIFAR-10 dataset while performing inference 4x faster than CapsNet. In addition, our proposed network is more robust at detecting images with affine transformations compared to CapsNet. We achieve 94.3% accuracy on the AffNIST dataset (compared to CapsNet 90.52%).
title LE-CapsNet: A Light and Enhanced Capsule Network
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2511.11708