Results 11 to 20 of about 69,407 (212)
Residual Capsule Network [PDF]
2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2019 Convolution Neural Network (CNN) has been the most influential innovations in the filed of Computer Vision. CNN have shown a substantial improvement in the field of Machine Learning. But they do come with their own set of drawbacks - CNN need a large dataset, hyperparameter tuning is nontrivial and importantly, they lose all the internal information ...
Sree Bala Shruthi Bhamidi +1 more
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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.
Marzieh Edraki +2 more
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Bipartite graph capsule network [PDF]
World Wide Web, 2022 AbstractGraphs have been widely adopted in various fields, where many graph models are developed. Most of previous research focuses on unipartite or homogeneous graph analysis. In this graphs, the relationships between the same type of entities are preserved in the graphs.
Xianhang Zhang +5 more
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Deep Tensor Capsule Network [PDF]
IEEE Access, 2020 Capsule network is a promising model in computer vision. It has achieved excellent results on simple datasets such as MNIST, but the performance deteriorates as data becomes complicated.
Kun Sun +3 more
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Attentive Octave Convolutional Capsule Network for Medical Image Classification
Applied Sciences, 2022 Medical image classification plays an essential role in disease diagnosis and clinical treatment. More and more research efforts have been dedicated to the design of effective methods for medical image classification.
Hong Zhang +4 more
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Orthopedic Research and ReviewsQian Li,1 Dinglin Li,1 Ciqiu Tian,2 Xiangjie Liu,1 Hui Wang,1 Hao Liu1 1Liyuan Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology, Tongji Medical College of Science and Technology, Wuhan, People’s Republic of ...
Li Q, Li D, Tian C, Liu X, Wang H, Liu H
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Quaternion Capsule Networks [PDF]
2020 25th International Conference on Pattern Recognition (ICPR), 2021 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 ...
Baris Özcan +2 more
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Limitation of capsule networks [PDF]
Pattern Recognition Letters, 2021 A recently proposed method in deep learning groups multiple neurons to capsules such that each capsule represents an object or part of an object. Routing algorithms route the output of capsules from lower-level layers to upper-level layers. In this paper, we prove that state-of-the-art routing procedures decrease the expressivity of capsule networks ...
David Peer +2 more
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UCaps Network Based on EM-Routing Algorithm for Medical Image Segmentation [PDF]
Jisuanji gongcheng, 2022 The existing medical image segmentation networks are limited in segmentation accuracy, and often lose image information as well as produce vague segmentation boundary.In this paper, we propose a multi-label image segmentation network named UCaps, which ...
WANG Wenxin, HE Yuhang, CHEN Gang
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Improved Two-Branch Capsule Network for Hyperspectral Image Classification [PDF]
Jisuanji kexue yu tansuo, 2022 The method based on the dual-channel capsule network extracts spectral information and spatial informa-tion separately in two channels, which not only retains the feature extraction method of the dual-channel convolu-tional neural network, but also ...
ZHANG Haitao, CHAI Simin
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