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A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 800-811
作者:  Snehasis Banerjee;  Tanushyam Chattopadhyay;  Utpal Garain
浏览  |  Adobe PDF(891Kb)  |  收藏  |  浏览/下载:235/65  |  提交时间:2021/02/22
Feature engineering  sensor data analysis  Internet of things (IoT) analytics  interpretable learning  automation.  
An Integrated MCI Detection Framework Based on Spectral-temporal Analysis 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 786-799
作者:  Jiao Yin;  Jinli Cao;  Siuly Siuly;  Hua Wang
浏览  |  Adobe PDF(2203Kb)  |  收藏  |  浏览/下载:183/52  |  提交时间:2021/02/22
Electroencephalogram (EEG)  dementia early detection  mild cognitive impairment (MCI)  stationary wavelet transformation (SWT)  support vector machine (SVM).  
Large-scale Data Collection and Analysis via a Gamified Intelligent Crowdsourcing Platform 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 4, 页码: 427-436
作者:  Simone Hantke;  Tobias Olenyi;  Christoph Hausner;  Tobias Appel;  Björn Schuller
浏览  |  Adobe PDF(1345Kb)  |  收藏  |  浏览/下载:135/46  |  提交时间:2021/02/22
Human computation  speech analysis  crowdsourcing  gamified data collection  survey.  
A Hybrid Time Frequency Response and Fuzzy Decision Tree for Non-stationary Signal Analysis and Pattern Recognition 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 3, 页码: 398-412
作者:  N. R. Nayak;  P. K. Dash;  R. Bisoi
浏览  |  Adobe PDF(1576Kb)  |  收藏  |  浏览/下载:154/50  |  提交时间:2021/02/22
Non-stationary signals  sparse S-transform (SST)  scaling method  fuzzy decision tree  pattern classification.  
An Approach to Reducing Input Parameter Volume for Fault Classifiers 期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 2, 页码: 199-212
作者:  Ann Smith;  Fengshou Gu;  Andrew D. Ball
浏览  |  Adobe PDF(1085Kb)  |  收藏  |  浏览/下载:156/67  |  提交时间:2021/02/22
Fault diagnosis  classification  variable clustering  data compression  big data.  
A Fast Surface Defect Detection Method Based on Background Reconstruction 期刊论文
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2019, 卷号: 21, 期号: 3, 页码: 363-375
作者:  Lv, Chengkan;  Zhang, Zhengtao;  Shen, Fei;  Zhang, Feng;  Su, Hu
Adobe PDF(2471Kb)  |  收藏  |  浏览/下载:377/57  |  提交时间:2020/03/30
Defect detection  Unsupervised learning  Background reconstruction  
Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2019, 卷号: 118, 页码: 231-238
作者:  Lu, Wei;  Zhong, Lianzhen;  Dong, Di;  Fang, Mengjie;  Dai, Qi;  Leng, Shaoyi;  Zhang, Liwen;  Sun, Wei;  Tian, Jie;  Zheng, Jianjun;  Jin, Yinhua
Adobe PDF(781Kb)  |  收藏  |  浏览/下载:435/82  |  提交时间:2019/12/16
Forecasting  Thyroid neoplasms  Lymphatic metastasis  
Day-Ahead Hourly Forecasting of Solar Generation Based on Cluster Analysis and Ensemble Model 期刊论文
IEEE ACCESS, 2019, 卷号: 7, 期号: 7, 页码: 112921-112930
作者:  Pan, Cheng;  Tan, Jie
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Cluster analysis  ensemble model  ridge regression  solar generation forecasting  
Dual L-1-Normalized Context Aware Tensor Power Iteration and Its Applications to Multi-object Tracking and Multi-graph Matching 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2019, 期号: 128, 页码: 33
作者:  Hu, Weiming;  Shi, Xinchu;  Zhou, Zongwei;  Xing, Junliang;  Ling, Haibin;  Maybank, Stephen
Adobe PDF(6300Kb)  |  收藏  |  浏览/下载:707/229  |  提交时间:2019/12/16
Multi-dimensional assignment  Context  hyper-context aware tensor power iteration  Multi-object tracking  Multi-graph matching  
Prognostic value of computed tomography radiomics features in patients with gastric cancer following curative resection 期刊论文
EUROPEAN RADIOLOGY, 2019, 卷号: 29, 期号: 6, 页码: 3079-3089
作者:  Li, Wuchao;  Zhang, Liwen;  Tian, Chong;  Song, Hui;  Fang, Mengjie;  Hu, Chaoen;  Zang, Yali;  Cao, Ying;  Dai, Shiyuan;  Wang, Fang;  Dong, Di;  Wang, Rongpin;  Tian, Jie
Adobe PDF(1951Kb)  |  收藏  |  浏览/下载:532/140  |  提交时间:2019/07/12
Multidetector computed tomography  Stomach neoplasms  Survival