Results 41 to 50 of about 51,131 (269)
Structural-parametric Synthesis of Capsule Neural Networks
Electronics and Control Systems, 2023 This work is dedicated to the structural-parametric synthesis of capsule neural networks. A methodology for structural-parametric synthesis of capsule neural networks has been developed, which includes the following algorithms: determining the most influential parameters of the capsule neural network, a hybrid machine learning algorithm.
Victor Sineglazov, Denys Kudriev
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A capsule-unified framework of deep neural networks for graphical programming [PDF]
Soft Computing, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yujian Li +3 more
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Learning Capsules for SAR Target Recognition
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Deep learning has been successfully utilized in synthetic aperture radar (SAR) automatic target recognition tasks and obtained state-of-the-art results. However, current deep learning algorithms do not perform well when SAR images are occluded, noisy, or
Yunrui Guo +4 more
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Will Capsule Networks overcome Convolutional Neural Networks on Pedestrian Walking Direction ?
2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019 Thousands of people are dying every year due to road accidents; in fact 23% of world fatal accidents are pedestrians related, where 40% of them occur in Africa as reported by the World Health Organisation (WHO). Predicting the walking direction of a pedestrian could help to avoid an eventual accident.
Safaâ Dafrallah +3 more
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CBIR system using Capsule Networks and 3D CNN for Alzheimer's disease diagnosis
Informatics in Medicine Unlocked, 2019 Alzheimer’s disease (AD) is an irreversible disorder of the brain related to loss of memory, commonly seen in the elderly and aging population. Implementation of revolutionary computer aided diagnosis techniques with Content Based Image Retrieval (CBIR ...
K.R. Kruthika +2 more
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IEEE Access, 2021 The improvement of remote sensing scene classification(RSSC) by effectively extracting discriminant representations for complex and diverse scenes remains a challenging task. The capsule network(CapsNet) can encode the spatial relationship of features in
Chunyuan Wang +4 more
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A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification
BiomimeticsTransfer learning is the act of using the data or knowledge in a problem to help solve different but related problems. In a brain computer interface (BCI), it is important to deal with individual differences between topics and/or tasks. A kind of capsule
Wei Zhang +3 more
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Capsule Networks Showed Excellent Performance in the Classification of hERG Blockers/Nonblockers
Frontiers in Pharmacology, 2020 Capsule networks (CapsNets), a new class of deep neural network architectures proposed recently by Hinton et al., have shown a great performance in many fields, particularly in image recognition and natural language processing. However, CapsNets have not
Yiwei Wang +8 more
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Machines, 2022 As scalar neurons of traditional neural networks promote dimension reduction caused by pooling, it is a difficult task to extract the high-dimensional spatial features and long-term correlation of pure signals from the noisy vibration signal.
Youming Wang, Gongqing Cao, Jiali Han
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SECaps: A Sequence Enhanced Capsule Model for Charge Prediction
, 2019 Automatic charge prediction aims to predict appropriate final charges according to the fact descriptions for a given criminal case. Automatic charge prediction plays a critical role in assisting judges and lawyers to improve the efficiency of legal ...
Chao-Lin Liu +9 more
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