Results 1 to 10 of about 5,268,113 (239)

Heart Murmur Classification Using a Capsule Neural Network [PDF]

Bioengineering, 2023
The healthcare industry has made significant progress in the diagnosis of heart conditions due to the use of intelligent detection systems such as electrocardiograms, cardiac ultrasounds, and abnormal sound diagnostics that use artificial intelligence ...
Yu-Ting Tsai, Yu-Hsuan Liu, Zi-Wei Zheng, Chih-Cheng Chen, Ming-Chih Lin   +4 more
doaj   +2 more sources

A Novel Capsule Based Hybrid Neural Network for Sentiment Classification

IEEE Access, 2019
Sentiment classification of short text is a challenging task because of limited contextual information. We propose a capsule-based hybrid neural network model which can obtain the implicit semantic information effectively.
Yongping Du, Xiaozheng Zhao, Meng He, Wenyang Guo   +3 more
doaj   +3 more sources

A Capsule Decision Neural Network Based on Transfer Learning for EEG Signal Classification

Biomimetics
Transfer learning is the act of using the data or knowledge in a problem to help solve different but related problems. In a brain computer interface (BCI), it is important to deal with individual differences between topics and/or tasks. A kind of capsule
Wei Zhang, Xianlun Tang, Xiaoyuan Dang, Mengzhou Wang   +3 more
doaj   +3 more sources

Multiscale Feature Aggregation Capsule Neural Network for Hyperspectral Remote Sensing Image Classification

Remote Sensing, 2022
Models based on capsule neural network (CapsNet), a novel deep learning method, have recently made great achievements in hyperspectral remote sensing image (HSI) classification due to their excellent ability to implicitly model the spatial relationship ...
Runmin Lei, Chunju Zhang, Xueying Zhang, Jianwei Huang, Zhenxuan Li, Wencong Liu, Hao Cui   +6 more
doaj   +3 more sources

Capsule neural network and its applications in drug discovery [PDF]

iScience
Summary: Deep learning holds great promise in drug discovery, yet its application is hindered by high labeling costs and limited datasets. Developing algorithms that effectively learn from sparsely labeled data is crucial.
Yiwei Wang, Binyou Wang, Jun Zou, Anguo Wu, Yuan Liu, Ying Wan, Jiesi Luo, Jianming Wu   +7 more
doaj   +2 more sources

DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network. [PDF]

Comput Biol Med, 2021
Quan H, Xu X, Zheng T, Li Z, Zhao M, Cui X.   +5 more
europepmc   +2 more sources

COVID-19 Diagnosis in Computerized Tomography (CT) and X-ray Scans Using Capsule Neural Network. [PDF]

Diagnostics (Basel), 2023
Akinyelu AA, Bah B.
europepmc   +2 more sources

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
doaj   +1 more source

Fault Diagnosis of Bearings with Small Sample Size Using Improved Capsule Network and Siamese Neural Network

Sensors
This paper addresses the challenges of low accuracy and long transfer learning time in small-sample bearing fault diagnosis, which are often caused by limited samples, high noise levels, and poor feature extraction.
Jarula Yasenjiang, Yang Xiao, Chao He, Luhui Lv, Wenhao Wang   +4 more
doaj   +3 more sources

The Fault Diagnosis of Rolling Bearings Is Conducted by Employing a Dual-Branch Convolutional Capsule Neural Network. [PDF]

Sensors (Basel)
Lu W, Liu J, Lin F.
europepmc   +2 more sources