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CASIA OpenIR

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Open set domain adaptation with latent structure discovery and kernelized classifier learning 期刊论文
NEUROCOMPUTING, 2023, 卷号: 531, 页码: 125-139
作者:  Tang, Yongqiang;  Tian, Lei;  Zhang, Wensheng
收藏  |  浏览/下载：46/0  |  提交时间：2023/11/17
Open set domain adaptation  Adaptive graph learning  Latent structure discovery  Kernelized classifier learning  
CNN-Based Broad Learning for Cross-Domain Emotion Classification 期刊论文
TSINGHUA SCIENCE AND TECHNOLOGY, 2023, 卷号: 28, 期号: 2, 页码: 360-369
作者:  Zeng, Rong;  Liu, Hongzhan;  Peng, Sancheng;  Cao, Lihong;  Yang, Aimin;  Zong, Chengqing;  Zhou, Guodong
收藏  |  浏览/下载：220/0  |  提交时间：2022/11/14
Measurement  Deep learning  Adaptation models  Feature extraction  Convolutional neural networks  Data mining  Task analysis  cross-domain emotion classification  CNN  broad learning  classifier  co-training  
ADTIDO: Detecting the Tired Deck Officer with Fusion Feature Methods 期刊论文
SENSORS, 2022, 卷号: 22, 期号: 17, 页码: 16
作者:  Li, Chenghao;  Fu, Yuhui;  Ouyang, Ruihong;  Liu, Yu;  Hou, Xinwen
收藏  |  浏览/下载：147/0  |  提交时间：2022/11/14
EEG  deck officer  fatigue detection  ECD-EEG fusion features  Bi-GRU neural network classifier  
Fuzzy C-Means Clustering Based Deep Patch Learning With Improved Interpretability for Classification Problems 期刊论文
IEEE ACCESS, 2022, 卷号: 10, 页码: 49873-49891
作者:  Huang, Yunhu;  Chen, Dewang;  Zhao, Wendi;  Lv, Yisheng
收藏  |  浏览/下载：164/0  |  提交时间：2022/07/25
Computational modeling  Training  Microwave integrated circuits  Deep learning  Data models  Artificial neural networks  Training data  Fuzzy c-means (FCM) clustering  maximal information coefficient (MIC)  random input (RI)  deep patch learning classifier  interpretability  
Belief Combination of Classifiers for Incomplete Data 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2022, 卷号: 9, 期号: 4, 页码: 652-667
作者:  Zuowei Zhang, Songtao Ye, Yiru Zhang, Weiping Ding, Hao Wang
Adobe PDF(1784Kb)  |  收藏  |  浏览/下载：167/55  |  提交时间：2022/03/09
Classifier fusion,classification,evidence theory,incomplete data,missing values  
A new two-layer nearest neighbor selection method for kNN classifier 期刊论文
KNOWLEDGE-BASED SYSTEMS, 2022, 卷号: 235, 页码: 14
作者:  Wang, Yikun;  Pan, Zhibin;  Dong, Jing
收藏  |  浏览/下载：142/0  |  提交时间：2021/12/28
kNN classifier  Two-layer nearest neighbor rule  First-layer neighborhood  Second-layer neighborhood  Extended neighborhood  
Hierarchical Fused Model With Deep Learning and Type-2 Fuzzy Learning for Breast Cancer Diagnosis 期刊论文
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 卷号: 28, 期号: 12, 页码: 3204-3218
作者:  Shen, Tianyu;  Wang, Jiangong;  Gou, Chao;  Wang, Fei-Yue
Adobe PDF(3530Kb)  |  收藏  |  浏览/下载：269/60  |  提交时间：2021/03/02
Image segmentation  Biomedical imaging  Fuzzy sets  Breast cancer  Breast cancer  deep learning (DL)  fuzzy classifier (FC)  interval type-2 possibilistic fuzzy c-means (IT2PFCM)  
Automatic Classification of Cardiac Arrhythmias Based on Hybrid Features and Decision Tree Algorithm 期刊论文
International Journal of Automation and Computing, 2020, 卷号: 17, 期号: 4, 页码: 551-561
作者:  Santanu Sahoo;  Asit Subudhi;  Manasa Dash;  Sukanta Sabut
浏览  |  Adobe PDF(1105Kb)  |  收藏  |  浏览/下载：108/34  |  提交时间：2021/02/22
Electrocardiogram (ECG)  cardiac arrhythmias  empirical mode decomposition (EMD)  variational mode decomposition (VMD)  hybrid features  decision tree classifier.  
Distinguishing Epileptiform Discharges From Normal Electroencephalograms Using Scale-Dependent Lyapunov Exponent 期刊论文
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2020, 卷号: 8, 页码: 14
作者:  Li, Qiong;  Gao, Jianbo;  Huang, Qi;  Wu, Yuan;  Xu, Bo
收藏  |  浏览/下载：154/0  |  提交时间：2021/01/07
EEG  epileptiform discharges  power spectral density (PSD)  scale-dependent Lyapunov exponent (SDLE)  random forest classifier  support vector machine (SVM)  
Multi-Domain Sentiment Classification with Classifier Combination 期刊论文
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2011, 卷号: 26, 期号: 1;1, 页码: 25-33
作者:  Li, Shou-Shan;  Huang, Chu-Ren;  Zong, Cheng-Qing
收藏  |  浏览/下载：7/0  |  提交时间：2020/10/27
Sentiment Classification  Multiple Classifier System  Multi-domain Learning