Results 41 to 50 of about 33,619 (260)
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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Decomposing word embedding with the capsule network [PDF]
Knowledge-Based Systems, 2021 Word sense disambiguation tries to learn the appropriate sense of an ambiguous word in a given context. The existing pre-trained language methods and the methods based on multi-embeddings of word did not explore the power of the unsupervised word embedding sufficiently.
Xin Liu 0054 +6 more
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EDC-Net: Edge Detection Capsule Network for 3D Point Clouds
Applied Sciences, 2021 Edge features in point clouds are prominent due to the capability of describing an abstract shape of a set of points. Point clouds obtained by 3D scanner devices are often immense in terms of size. Edges are essential features in large scale point clouds
Dena Bazazian, M. Eulàlia Parés
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CapSurv: Capsule Network for Survival Analysis With Whole Slide Pathological Images
IEEE Access, 2019 Survival analysis is a branch of statistics to analyze the time duration that is expected until some events of interest happen, like the death in the organisms of biology.
Bo Tang, Ao Li, Bin Li, Minghui Wang
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Next-Generation Neural Networks: Capsule Networks With Routing-by-Agreement for Text Classification
IEEE Access, 2021 These days, neural networks constantly prove their high capacity for nearly every application case and are considered as key technology for learning systems.
Nikolai A. K. Steur, Friedhelm Schwenker
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Image Colorization by Capsule Networks [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2019 Accepted to New Trends in Image Restoration and Enhancement(NTIRE) Workshop at CVPR ...
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Class-Variational Learning With Capsule Networks for Deep Entity-Subspace Clustering
IEEE Access, 2023 The progression of deep clustering techniques in the recent years emphasizes the need for unsupervised representation learning methods that build lower-dimensional embeddings within expressive latent feature spaces.
Nikolai A. K. Steur, Friedhelm Schwenker
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Wasserstein Routed Capsule Networks
CoRR, 2020 8 pages, 3 ...
Alexander Fuchs 0009, Franz Pernkopf
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The Multi-Lane Capsule Network [PDF]
IEEE Signal Processing Letters, 2019 We introduce multi-lane capsule networks (MLCN), which are a separable and resource efficient organization of capsule networks (CapsNet) that allows parallel processing while achieving high accuracy at reduced cost. A MLCN is composed of a number of (distinct) parallel lanes , each contributing to a dimension of the result, trained using the routing ...
Vanderson Martins do Rosario +2 more
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2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 In this paper, we propose 3D point-capsule networks, an auto-encoder designed to process sparse 3D point clouds while preserving spatial arrangements of the input data. 3D capsule networks arise as a direct consequence of our novel unified 3D auto-encoder formulation.
Yongheng Zhao +3 more
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