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A Deep High-Order Tensor Sparse Representation for Hyperspectral Image Classification Journal article
Cheng, Chunbo, Zhang, Liming, Li, Hong, Cui, Wenjing, Gao, Junbin, Cun, Yuxiao. A Deep High-Order Tensor Sparse Representation for Hyperspectral Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2024, 62, 5521416.
Authors:  Cheng, Chunbo;  Zhang, Liming;  Li, Hong;  Cui, Wenjing;  Gao, Junbin; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:7.5/7.6 | Submit date：2024/08/05
Convolutional Neural Network (Cnn)  Deep High-order Tensor Sparse Representation (Sr)  Deep Learning  Graph-based Learning (Gsl)  Hyperspectral Image (Hsi) Classification  
Improving BOTDA Performance Based on Differential Pulsewidth Pair and FFDNet Journal article
Ge, Xiaopeng, Wang, Tao, Zhang, Qian, Peng, Jiaxin, Zhu, Yaqi, Zhang, Yongqi, Zhang, Jianzhong, Qiao, Lijun, Zhang, Mingjiang. Improving BOTDA Performance Based on Differential Pulsewidth Pair and FFDNet[J]. IEEE Sensors Journal, 2024, 24(10), 16137-16144.
Authors:  Ge, Xiaopeng;  Wang, Tao;  Zhang, Qian;  Peng, Jiaxin;  Zhu, Yaqi; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.3/4.2 | Submit date：2024/06/05
Brillouin Optical Time Domain Analysis (Botda)  Deep Learning  Differential Pulsewidth Pair (Dpp)  Fast And Flexible Denoising Convolutional Neural Network (Ffdnet)  
MASK-CNN-Transformer for real-time multi-label weather recognition Journal article
Chen, Shengchao, Shu, Ting, Zhao, Huan, Tang, Yuan Yan. MASK-CNN-Transformer for real-time multi-label weather recognition[J]. Knowledge-Based Systems, 2023, 278, 110881.
Authors:  Chen, Shengchao;  Shu, Ting;  Zhao, Huan;  Tang, Yuan Yan
Favorite | TC[WOS]:6 TC[Scopus]:7  IF:7.2/7.4 | Submit date：2023/09/22
Convolutional Neural Network  Deep Learning  Multi-label Weather Recognition  Transformer  
Probabilistic Seismic Response Prediction of Three-Dimensional Structures Based on Bayesian Convolutional Neural Network Journal article
Tianyu Wang, Huile Li, Mohammad Noori, Ramin Ghiasi, Wael A. Altabey. Probabilistic Seismic Response Prediction of Three-Dimensional Structures Based on Bayesian Convolutional Neural Network[J]. Sensors, 2022, 22(10), 3775.
Authors:  Tianyu Wang;  Huile Li;  Mohammad Noori;  Ramin Ghiasi;  Wael A. Altabey
Favorite | TC[WOS]:15 TC[Scopus]:21  IF:3.4/3.7 | Submit date：2022/08/02
Bayesian Deep Learning  Convolutional Neural Network  Random Vibration Of Structures  Seismic Response  
Two-view attention-guided convolutional neural network for mammographic image classification Journal article
Lilei Sun, Jie Wen, Junqian Wang, Yong Zhao, Bob Zhang, Jian Wu, Yong Xu. Two-view attention-guided convolutional neural network for mammographic image classification[J]. CAAI Transactions on Intelligence Technology, 2022, 8(2), 453-467.
Authors:  Lilei Sun;  Jie Wen;  Junqian Wang;  Yong Zhao;  Bob Zhang; et al.
Favorite | TC[WOS]:6 TC[Scopus]:8  IF:8.4/6.7 | Submit date：2022/05/17
Convolutional Neural Network  Deep Learning  Mammographic Image  Medical Image Processing  
NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote-Sensing Imagery Journal article
Lu, Ming, Fang, Leyuan, Li, Muxing, Zhang, Bob, Zhang, Yi, Ghamisi, Pedram. NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote-Sensing Imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60.
Authors:  Lu, Ming;  Fang, Leyuan;  Li, Muxing;  Zhang, Bob;  Zhang, Yi; et al.
Favorite | TC[WOS]:25 TC[Scopus]:36  IF:7.5/7.6 | Submit date：2022/05/17
Convolutional Neural Network (Cnn)  Deep Learning  Semantic Segmentation  Water Extraction  Weak Supervision  
Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network Journal article
Chen, Jiarui, Si, Yain Whar, Un, Chon Wai, Siu, Shirley W.I.. Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network[J]. Journal of Cheminformatics, 2021, 13(1).
Authors:  Chen, Jiarui;  Si, Yain Whar;  Un, Chon Wai;  Siu, Shirley W.I.
Favorite | TC[WOS]:30 TC[Scopus]:37  IF:7.1/9.3 | Submit date：2021/12/08
Admet  Chemical Toxicity  Deep Learning  Graph Convolutional Neural Network  Mean Teacher  Semi-supervised Learning  Tox21  
MIDCAN: A multiple input deep convolutional attention network for Covid-19 diagnosis based on chest CT and chest X-ray Journal article
Zhang, Yu Dong, Zhang, Zheng, Zhang, Xin, Wang, Shui Hua. MIDCAN: A multiple input deep convolutional attention network for Covid-19 diagnosis based on chest CT and chest X-ray[J]. PATTERN RECOGNITION LETTERS, 2021, 150, 8-16.
Authors:  Zhang, Yu Dong;  Zhang, Zheng;  Zhang, Xin;  Wang, Shui Hua
Favorite | TC[WOS]:69 TC[Scopus]:83  IF:3.9/4.2 | Submit date：2021/12/08
Deep Learning  Data Harmonization  Multiple Input  Convolutional Neural Network  Automatic Differentiation  Covid-19  Chest Ct  Chest X-ray  Multimodality  
Deep learning-based crack identification for steel pipelines by extracting features from 3d shadow modeling Journal article
Altabey, Wael A., Noori, Mohammad, Wang, Tianyu, Ghiasi, Ramin, Wu, Zhishen. Deep learning-based crack identification for steel pipelines by extracting features from 3d shadow modeling[J]. Applied Sciences (Switzerland), 2021, 11(13), 6063.
Authors:  Altabey, Wael A.;  Noori, Mohammad;  Wang, Tianyu;  Ghiasi, Ramin;  Wu, Zhishen
Favorite | TC[WOS]:19 TC[Scopus]:28  IF:2.5/2.7 | Submit date：2021/12/08
3d Shadow Modeling  Automatic Crack Identification  Convolutional Neural Network (Cnn)  Deep Learning  Structural Health Monitoring (Shm)  
Deep Learning-Based Crack Identification for Steel Pipelines by Extracting Features from 3D Shadow Modeling Journal article
Altabey, W. A., Noori, M., Wang, T., Ghiasi, R.. Deep Learning-Based Crack Identification for Steel Pipelines by Extracting Features from 3D Shadow Modeling[J]. Applied Sciences, 2021, 1-21.
Authors:  Altabey, W. A.;  Noori, M.;  Wang, T.;  Ghiasi, R.
Favorite |   IF:2.5/2.7 | Submit date：2022/08/30
Deep Learning  Automatic Crack Identification  Convolutional Neural Network (Cnn)  3d Shadow Modeling  Structural Health Monitoring (Shm)