Results 51 to 60 of about 69,407 (212)
Wasserstein Routed Capsule Networks
CoRR, 2020 8 pages, 3 ...
Alexander Fuchs 0009, Franz Pernkopf
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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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Image Super-Resolution Using Capsule Neural Networks
IEEE Access, 2020 Convolutional neural networks (CNNs) have been widely applied in super-resolution (SR) and other image restoration tasks. Recently, Hinton et al. proposed capsule neural networks to resolve the problem of viewpoint variations in image classification ...
Jui-Ting Hsu, Chih-Hung Kuo, De-Wei Chen
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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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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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Hyperparameter optimisation for Capsule Networks [PDF]
EAI Endorsed Transactions on Cloud Systems, 2019 Convolutional Neural Networks and its contemporary variants have proven to be ruling benchmarks for most image processing tasks but resort to pooling techniques and routing mechanisms that affect classification accuracy and lose spatial relationship information between involved data points.
Gagana B, S Natarajan
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Text classification model based on static routing and grouped capsule network
四川大学学报. 自然科学版, 2021 The use of capsule network in the fields of image and language have progressed tremendously over the past few years, with the extensive research of the capsule network.
ZHU Hai-Jing +4 more
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Hierarchical Graph Capsule Network
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 Graph Neural Networks (GNNs) draw their strength from explicitly modeling the topological information of structured data. However, existing GNNs suffer from limited capability in capturing the hierarchical graph representation which plays an important role in graph classification.
Jinyu Yang +6 more
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Towards Efficient Capsule Networks
2022 IEEE International Conference on Image Processing (ICIP), 2022 From the moment Neural Networks dominated the scene for image processing, the computational complexity needed to solve the targeted tasks skyrocketed: against such an unsustainable trend, many strategies have been developed, ambitiously targeting performance's preservation.
Renzulli, Riccardo, Grangetto, Marco
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Road marking extraction in UAV imagery using attentive capsule feature pyramid network
International Journal of Applied Earth Observations and Geoinformation, 2022 Accurately and precisely delineating road-markings from very high spatial resolution unmanned aerial vehicle (UAV) images face many challenges, such as complex scenarios, diverse road marking sizes and shapes, and absent and occluded road markings.
Haiyan Guan +6 more
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