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Intelligent fault diagnosis of train bearing based on ISTOA-VMD and SE-WDCNN 期刊论文
JOURNAL OF VIBRATION AND CONTROL, 2023, 页码: 12
作者:  He, Deqiang;  Zou, Xueyan;  Jin, Zhenzhen;  Yan, Jingren;  Ren, Chonghui;  Zhou, Jixu
收藏  |  浏览/下载：81/0  |  提交时间：2023/12/07
intelligent fault diagnosis  train bearing  improved sooty tern optimization algorithm  variational mode decomposition  deep convolutional neural network  
Recovering Gravity from Satellite Altimetry Data Using Deep Learning Network 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2023, 卷号: 61, 页码: 11
作者:  Zhu, Chengcheng;  Yang, Lei;  Bian, Hongwei;  Li, Houpu;  Guo, Jinyun;  Liu, Na;  Lin, Lina
收藏  |  浏览/下载：175/0  |  提交时间：2023/12/13
Gravity  Deep learning  Sea measurements  Satellites  Underwater vehicles  Training  Data models  gravity anomaly  multichannel convolutional neural network (MCCNN)  satellite altimetry  Index Terms  submarine topography  
Recovering Bathymetry From Satellite Altimetry-Derived Gravity by Fully Connected Deep Neural Network 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 卷号: 20, 页码: 5
作者:  Yang, Lei;  Liu, Min;  Liu, Na;  Guo, Jinyun;  Lin, Lina;  Zhang, Yuyuan;  Du, Xing;  Xu, Yongsheng;  Zhu, Chengcheng;  Wang, Yongkang
收藏  |  浏览/下载：225/0  |  提交时间：2023/12/07
Gravity  Bathymetry  Satellites  Geology  Altimetry  Geologic measurements  Sea measurements  convolutional neural network (CNN)  fully connected deep neural network (FC-DNN)  gravity  gravity-geological method  satellite altimetry  
Tropical Cyclone Intensity Estimation From Geostationary Satellite Imagery Using Deep Convolutional Neural Networks 期刊论文
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 卷号: 60, 页码: 16
作者:  Wang, Chong;  Zheng, Gang;  Li, Xiaofeng;  Xu, Qing;  Liu, Bin;  Zhang, Jun
Adobe PDF(4821Kb)  |  收藏  |  浏览/下载：281/0  |  提交时间：2022/02/18
Estimation  Ocean temperature  Clouds  Tropical cyclones  Cyclones  Training  Geostationary satellites  Convolutional neural network (CNN)  deep learning  remote sensing  tropical cyclone (TC)  
A Novel Marine Oil Spillage Identification Scheme Based on Convolution Neural Network Feature Extraction From Fully Polarimetric SAR Imagery 期刊论文
IEEE ACCESS, 2020, 卷号: 8, 页码: 59801-59820
作者:  Song, Dongmei;  Zhen, Zongjin;  Wang, Bin;  Li, Xiaofeng;  Gao, Le;  Wang, Ning;  Xie, Tao;  Zhang, Ting
Adobe PDF(5827Kb)  |  收藏  |  浏览/下载：262/0  |  提交时间：2020/09/23
Marine oil spill  RADARSAT-2  PolSAR  deep learning  feature extraction  convolutional neural network (CNN)