Segment-based Features
Segment-Based Features is a time series feature extraction method that derives descriptive characteristics by partitioning a time series into contiguous subsequences and computing statistical or structural metrics from each segment.
120
Publications
7.8K
Citations
410
Authors
204
Institutions
Publications per year
2017–2026
39
120
Deep Contrast Learning for Salient Object Detection
Guanbin Li, Yizhou Yu · 2016 · 732 citations
Extracting Interpretable Features for Early Classification on Time Series
Zhengzheng Xing, Jian Pei, Philip S. Yu et al. · 2011 · 176 citations
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204

University of Twente
Enschede, The Netherlands
4 h-index
10 publications
391 citations
National University of Singapore
Singapore, Singapore
3 h-index
7 publications
188 citations
Taizhou University
Taizhou, China
3 h-index
9 publications
1.4K citations
RTX (United States)
Arlington, United States
3 h-index
8 publications
509 citations
University of Maryland, College Park
College Park, United States
2 h-index
4 publications
143 citations
Institute of Automation
Beijing, China
2 h-index
4 publications
72 citations
University of Southern California
Los Angeles, United States
2 h-index
3 publications
83 citations
Centre for Quantum Computation and Communication Technology
Sydney, Australia
2 h-index
6 publications
171 citations
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TAC · 4 publications · 298 citations
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4 publications · 99 citations
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Repository · 3 publications · 333 citations
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3 publications · 200 citations
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2 publications · 79 citations
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