Results 31 to 40 of about 21,605 (294)
Multi-branch RA Capsule Network and Its Application in Image Classification [PDF]
Jisuanji kexue, 2022 Capsule Network is a new type of deep neural network that uses vectors to express information of image feature and overcomes two major problems of convolutional neural networks by introducing dynamic routing algorithms.First,convolutional neural networks
WU Lin, SUN Jing-yu
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Residual Vector Capsule: Improving Capsule by Pose Attention
IEEE Access, 2021 The convolutional neural network has significantly improved the accuracy of image recognition; however, it performs in a fragile manner when we apply viewpoint transformation or add noise to the image.
Ning Xie, Xiaoxia Wan
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Attention enhanced capsule network for text classification by encoding syntactic dependency trees with graph convolutional neural network [PDF]
PeerJ Computer Science, 2022 Text classification is a fundamental task in many applications such as topic labeling, sentiment analysis, and spam detection. The text syntactic relationship and word sequence are important and useful for text classification.
Xudong Jia, Li Wang
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Robot Communication: Network Traffic Classification Based on Deep Neural Network
Frontiers in Neurorobotics, 2021 With the rapid popularization of robots, the risks brought by robot communication have also attracted the attention of researchers. Because current traffic classification methods based on plaintext cannot classify encrypted traffic, other methods based ...
Mengmeng Ge, Xiangzhan Yu, Likun Liu
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GE: Portuguese Journal of Gastroenterology, 2021 Introduction: Capsule endoscopy has revolutionized the management of patients with obscure gastrointestinal bleeding. Nevertheless, reading capsule endoscopy images is time-consuming and prone to overlooking significant lesions, thus limiting its ...
Miguel Mascarenhas Saraiva +8 more
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Examining the Benefits of Capsule Neural Networks
CoRR, 2020 Capsule networks are a recently developed class of neural networks that potentially address some of the deficiencies with traditional convolutional neural networks. By replacing the standard scalar activations with vectors, and by connecting the artificial neurons in a new way, capsule networks aim to be the next great development for computer vision ...
Arjun Punjabi +2 more
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Scientific Reports, 2023 Fully convolutional neural network has shown advantages in the salient object detection by using the RGB or RGB-D images. However, there is an object-part dilemma since most fully convolutional neural network inevitably leads to an incomplete ...
Kun Xu, Jichang Guo
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Research of Short Text Multi-intent Detection with Capsule Network
Jisuanji kexue yu tansuo, 2020 Intent detection is a key sub-task of spoken language understanding in human-machine dialogue system. Considering the problem of user's multi-intent expressed, a multi-intent classifier based on single-intent marker is constructed by using capsule ...
LIU Jiao, LI Yanling, LIN Min
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Simplified Routing Mechanism for Capsule Networks
Algorithms, 2023 Classifying digital images using neural networks is one of the most fundamental tasks within the field of artificial intelligence. For a long time, convolutional neural networks have proven to be the most efficient solution for processing visual data ...
János Hollósi +2 more
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VIOLA jones algorithm with capsule graph network for deepfake detection [PDF]
PeerJ Computer Science, 2023 DeepFake is a forged image or video created using deep learning techniques. The present fake content of the detection technique can detect trivial images such as barefaced fake faces.
Venkatachalam K +2 more
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