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An Adaptive Deep Metric Learning Loss Function for Class-Imbalance Learning via Intraclass Diversity and Interclass Distillation Journal article
Du,Jie, Zhang,Xiaoci, Liu,Peng, Vong,Chi Man, Wang,Tianfu. An Adaptive Deep Metric Learning Loss Function for Class-Imbalance Learning via Intraclass Diversity and Interclass Distillation[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, 1-15.
Authors:  Du,Jie;  Zhang,Xiaoci;  Liu,Peng;  Vong,Chi Man;  Wang,Tianfu
Favorite | TC[WOS]:2 TC[Scopus]:7  IF:10.2/10.4 | Submit date：2023/08/03
Class-imbalance Learning (Cil)  Correlation  Deep Metric Learning (Dml)  Diverse And Discriminant Feature  Face Recognition  Feature Extraction  Learning Systems  Loss Function With Adaptive Weights  Semantic Correlations Between Classes  Semantics  Task Analysis  Ultrasonic Imaging  
Bi-deformation-UNet: recombination of differential channels for printed surface defect detection Journal article
Chen, Ziyang, Huang, Guoheng, Wang, Ying, Qiu, Junhao, Yang, Fan, Yu, Zhiwen, Pun, Chi Man, Ling, Wing Kuen. Bi-deformation-UNet: recombination of differential channels for printed surface defect detection[J]. VISUAL COMPUTER, 2022, 39, 3995 - 4013.
Authors:  Chen, Ziyang;  Huang, Guoheng;  Wang, Ying;  Qiu, Junhao;  Yang, Fan; et al.
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:3.0/3.0 | Submit date：2022/08/05
Subtle Defects  Object Detection  Edge Detection  Metric Learning  Class-imbalance  
Shift-channel attention and weighted-region loss function for liver and dense tumor segmentation Journal article
Li, Jiajian, Huang, Guoheng, He, Junlin, Chen, Ziyang, Pun, Chi Man, Yu, Zhiwen, Ling, Wing Kuen, Liu, Lizhi, Zhou, Jian, Huang, Jinhua. Shift-channel attention and weighted-region loss function for liver and dense tumor segmentation[J]. Medical Physics, 2022, 49(11), 7193-7206.
Authors:  Li, Jiajian;  Huang, Guoheng;  He, Junlin;  Chen, Ziyang;  Pun, Chi Man; et al.
Favorite | TC[WOS]:2 TC[Scopus]:2  IF:3.2/3.9 | Submit date：2022/08/05
Class Imbalance Learning  Multiscale Contextual Information  Shift-channel Attention  Weighted-region Loss Function  
Self-Adaptive Multiprototype-Based Competitive Learning Approach: A k-Means-Type Algorithm for Imbalanced Data Clustering Journal article
Lu, Yang, Cheung, Yiu Ming, Tang, Yuan Yan. Self-Adaptive Multiprototype-Based Competitive Learning Approach: A k-Means-Type Algorithm for Imbalanced Data Clustering[J]. IEEE Transactions on Cybernetics, 2021, 51(3), 1598-1612.
Authors:  Lu, Yang;  Cheung, Yiu Ming;  Tang, Yuan Yan
Favorite | TC[WOS]:41 TC[Scopus]:51  IF:9.4/10.3 | Submit date：2021/12/07
Class Imbalance Learning  Competitive Learning  Data Clustering  Internal Validation Measure  K-means-type Algorithm  Multiprototype Clustering  
Mining massive e-health data streams for IoMT enabled healthcare systems Journal article
Affan Ahmed Toor, Muhammad Usman, Farah Younas, Alvis Cheuk M. Fong, Sajid Ali Khan, Simon Fong. Mining massive e-health data streams for IoMT enabled healthcare systems[J]. Sensors (Switzerland), 2020, 20(7), 2131.
Authors:  Affan Ahmed Toor;  Muhammad Usman;  Farah Younas;  Alvis Cheuk M. Fong;  Sajid Ali Khan; et al.
Favorite | TC[WOS]:21 TC[Scopus]:36  IF:3.4/3.7 | Submit date：2021/03/09
Data Stream Mining  Iomt  Concept Drift  Class Imbalance  Machine Learning  
Postboosting using Extended G-mean for Online Sequential Multiclass Imbalance Learning Journal article
Vong, C. M., Du, J., Wong, C. M., Cao, J. W.. Postboosting using Extended G-mean for Online Sequential Multiclass Imbalance Learning[J]. IEEE Transactions on Neural Networks and Learning Systems (SCI-E), 2018, 6163-6177.
Authors:  Vong, C. M.;  Du, J.;  Wong, C. M.;  Cao, J. W.
Favorite |  | Submit date：2022/08/09
Online Sequential Learning  Multi-class Imbalance Learning  Dynamic Changing Distribution  Imbalance Class Distribution  Extreme Learning Machine  
Postboosting Using Extended G-Mean for Online Sequential Multiclass Imbalance Learning Journal article
Vong, Chi-Man, Du, Jie, Wong, Chi-Man, Cao, Jiu-Wen. Postboosting Using Extended G-Mean for Online Sequential Multiclass Imbalance Learning[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29(12), 6163-6177.
Authors:  Vong, Chi-Man;  Du, Jie;  Wong, Chi-Man;  Cao, Jiu-Wen
Favorite | TC[WOS]:22 TC[Scopus]:30  IF:10.2/10.4 | Submit date：2019/01/17
Dynamic Changing Distribution  Extreme Learning Machine  Imbalance Class Distribution  Multiclass Imbalance Learning  Online Sequential Learning  
Tackling class overlap and imbalance problems in software defect prediction Journal article
Chen, Lin, Fang, Bin, Shang, Zhaowei, Tang, Yuanyan. Tackling class overlap and imbalance problems in software defect prediction[J]. SOFTWARE QUALITY JOURNAL, 2018, 26(1), 97-125.
Authors:  Chen, Lin;  Fang, Bin;  Shang, Zhaowei;  Tang, Yuanyan
Favorite | TC[WOS]:69 TC[Scopus]:90  IF:1.7/1.9 | Submit date：2018/10/30
Software Defect Prediction  Class Imbalance  Class Overlap  Machine Learning  
Hybrid Sampling with Bagging for Class Imbalance Learning Conference paper
Yang Lu, Yiu-ming Cheung, Yuan Yan Tang. Hybrid Sampling with Bagging for Class Imbalance Learning[C]:SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, 2016, 14-26.
Authors:  Yang Lu;  Yiu-ming Cheung;  Yuan Yan Tang
Favorite | TC[WOS]:29 TC[Scopus]:25 | Submit date：2019/02/11
Class Imbalance Learning  Ensemble Method  Hybrid Sampling  Sampling Method