Chien-Hsing Chou

1.5k citations
58 papers · 1.1k indexed · h-index 13

Chien-Hsing Chou

53 papers receiving 963 citations

Peers

Chien-Hsing Chou
Comparison fields: 5 of 113
  • Computer Vision and Pattern Recognition 459
  • Human-Computer Interaction 116
  • Artificial Intelligence 492
  • Media Technology 96
  • Signal Processing 95
Replace Paolo Gastaldo with:
Paolo Gastaldo Italy
Hong-Han Shuai Taiwan
Mohammad Rahmati Iran
Mohamad Ivan Fanany Indonesia
Haoxiang Wang China
Ilya Makarov Russia
Siome Goldenstein Brazil
Denis Gračanin United States
Vineeth N Balasubramanian India
Chien-Hsing Chou relative to Paolo Gastaldo Italy Paolo Gastaldo's profile →
Citations per field
00.5×1.5×2.4×
Paolo Gastaldo · 1×
Citations per year

Countries citing papers authored by Chien-Hsing Chou

Since Specialization
Citations

This map shows the geographic impact of Chien-Hsing Chou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chien-Hsing Chou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chien-Hsing Chou more than expected).

Fields of papers citing papers by Chien-Hsing Chou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chien-Hsing Chou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chien-Hsing Chou. The network helps show where Chien-Hsing Chou may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Chien-Hsing Chou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chien-Hsing Chou Line = papers co-authored together Chien-Hsing Chou links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20242
4 20241
5 20211
6
Interactive Teaching Aids Integrating Building Blocks and Programming Logic
20192
7 20171
8 20152
9 20111
10 20118
11 20111
12 200911
13 20086
14 200694
15 200623
16 20051
17 20053
18 20054
19 2001262
20 200111

About Chien-Hsing Chou

Chien-Hsing Chou is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 58 papers that have together received 1.1k indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (11 papers), Tactile and Sensory Interactions (10 papers), Image Retrieval and Classification Techniques (9 papers), Teleoperation and Haptic Systems (7 papers), Handwritten Text Recognition Techniques (7 papers), Advanced Image and Video Retrieval Techniques (6 papers), Hand Gesture Recognition Systems (6 papers) and Face and Expression Recognition (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (459 citations), Human-Computer Interaction (116 citations) and Artificial Intelligence (492 citations). Chien-Hsing Chou has collaborated with scholars based in Taiwan. Frequent co-authors include Mu‐Chun Su, Fu Chang, Eugene Lai, Shih-Yu Chu, Ping-Hsuan Han, Yu-Sheng Su, Chin-Chin Lin, Yi‐Ping Hung, Chi‐Yi Tsai and Hsiao-Te Chang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Expert Systems with Applications and IEEE Access.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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