From Auto-encoders to Capsule Networks: A Survey

Author:

El Alaoui-Elfels Omaima,Gadi Taoufiq

Abstract

Convolutional Neural Networks are a very powerful Deep Learning structure used in image processing, object classification and segmentation. They are very robust in extracting features from data and largely used in several domains. Nonetheless, they require a large number of training datasets and relations between features get lost in the Max-pooling step, which can lead to a wrong classification. Capsule Networks(CapsNets) were introduced to overcome these limitations by extracting features and their pose using capsules instead of neurons. This technique shows an impressive performance in one-dimensional, two-dimensional and three-dimensional datasets as well as in sparse datasets. In this paper, we present an initial understanding of CapsNets, their concept, structure and learning algorithm. We introduce the progress made by CapsNets from their introduction in 2011 until 2020. We compare different CapsNets series architectures to demonstrate strengths and challenges. Finally, we quote different implementations of Capsule Networks and show their robustness in a variety of domains. This survey provides the state-of-theartof Capsule Networks and allows other researchers to get a clear view of this new field. Besides, we discuss the open issues and the promising directions of future research, which may lead to a new generation of CapsNets.

Publisher

EDP Sciences

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Understanding the Dynamics of Sparse Coding in Auto-Encoders for Cancer Detection;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29

2. Capsule network-based disease classification for Vitis Vinifera leaves;Neural Computing and Applications;2023-10-07

3. Capsule networks for computer vision applications: a comprehensive review;Applied Intelligence;2023-06-14

4. Enhanced Exploration of Neural Network Models for Indoor Human Monitoring;2023 9th International Workshop on Advances in Sensors and Interfaces (IWASI);2023-06-08

5. VIOLA jones algorithm with capsule graph network for deepfake detection;PeerJ Computer Science;2023-04-13

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