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Medical imaging analysis with artificial neural networks [PDF]
, 2010 Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection ...
Jiang, J., Ren, Jinchang, Trundle, P.
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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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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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Remote Sensing, 2021 In order to overcome the disadvantages of convolution neural network (CNN) in the current hyperspectral image (HSI) classification/segmentation methods, such as the inability to recognize the rotation of spatial objects, the difficulty to capture the ...
Le Sun +4 more
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ROBUSTCAPS: A TRANSFORMATION-ROBUST CAPSULE NETWORK FOR IMAGE CLASSIFICATION [PDF]
ICTACT Journal on Image and Video Processing, 2023 Geometric transformations of the training data as well as the test data present challenges to the use of deep neural networks to vision-based learning tasks.
Sai Raam Venkataraman +2 more
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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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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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