Results 21 to 30 of about 156,643 (272)
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Convolutional neural networks (CNNs) have become a key asset to most of fields in AI. Despite their successful performance, CNNs suffer from a major drawback. They fail to capture the hierarchy of spatial relation among different parts of an entity. As a remedy to this problem, the idea of capsules was proposed by Hinton.
Edraki, Marzieh +2 more
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Capsule Network with Shortcut Routing
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2021 8 pages, published at IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences E104.A(8)
Vu, Dang Thanh +3 more
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Coal mine information comprehensive perception and intelligent decision system
Gong-kuang zidonghua, 2020 Aiming at problems of poor information perception ability and low decision level in coal mine safety production, a coal mine information comprehensive perception and intelligent decision system was proposed, which was composed of capsule network layer ...
LI Tengfei, LI Changyou, LI Jingzhao
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Breaking CAPTCHA with Capsule Networks
Neural Networks, 2022 Convolutional Neural Networks have achieved state-of-the-art performance in image classification. Their lack of ability to recognise the spatial relationship between features, however, leads to misclassification of the variants of the same image. Capsule Networks were introduced to address this issue by incorporating the spatial information of image ...
Ionela Georgiana Mocanu +2 more
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Capsule-LPI: a LncRNA–protein interaction predicting tool based on a capsule network
BMC Bioinformatics, 2021 Background Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA–protein interactions (LPIs) is key to understanding lncRNA functions.
Ying Li +5 more
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Change Capsule Network for Optical Remote Sensing Image Change Detection
Remote Sensing, 2021 Change detection based on deep learning has made great progress recently, but there are still some challenges, such as the small data size in open-labeled datasets, the different viewpoints in image pairs, and the poor similarity measures in feature ...
Quanfu Xu +3 more
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Remote Sensing, 2019 Capsule networks can be considered to be the next era of deep learning and have recently shown their advantages in supervised classification. Instead of using scalar values to represent features, the capsule networks use vectors to represent features ...
Kaiqiang Zhu +4 more
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, 2020 Capsules are grouping of neurons that allow to represent sophisticated information of a visual entity such as pose and features. In the view of this property, Capsule Networks outperform CNNs in challenging tasks like object recognition in unseen viewpoints, and this is achieved by learning the transformations between the object and its parts with the ...
��zcan, Bar���� +2 more
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Neural Processing Letters, 2020 Capsule network (CapsNet) was introduced as an enhancement over convolutional neural networks, supplementing the latter's invariance properties with equivariance through pose estimation. CapsNet achieved a very decent performance with a shallow architecture and a significant reduction in parameters count.
Mohammed Amer, Tomás Maul
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Retrieval of Chemical Oxygen Demand through Modified Capsule Network Based on Hyperspectral Data
Applied Sciences, 2019 This study focuses on the retrieval of chemical oxygen demand (COD) in the Baiyangdian area in North China, using a modified capsule network. Herein, the capsule model was modified to analyze the regression relationship between 1-D hyperspectral data and
Chubo Deng, Lifu Zhang, Yi Cen
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