Ming‐Ching Chang

5.5k citations
135 papers · 3.7k · 2 hit papers · h-index 28

Impact in

    • Video Surveillance and Tracking Methods
    • Digital Media Forensic Detection
    • Advanced Neural Network Applications
    • Human Pose and Action Recognition
    • Context-Aware Activity Recognition Systems
    • Autonomous Vehicle Technology and Safety

Papers in

Ming‐Ching Chang

122 papers receiving 3.5k citations

Ming‐Ching Chang's Hit Papers

UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking 2020 · 498 citations
4980+2+5Years since publication200400600

Peers

Ming‐Ching Chang
Comparison fields: 5 of 107
  • Computer Vision and Pattern Recognition 2.8k
  • Automotive Engineering 97
  • Artificial Intelligence 234
  • Radiology, Nuclear Medicine and Imaging 141
  • Human-Computer Interaction 42
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Ming‐Ching Chang relative to Ruimao Zhang China Ruimao Zhang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ming‐Ching Chang

Since Specialization
Citations

This map shows the geographic impact of Ming‐Ching Chang'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 Ming‐Ching Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming‐Ching Chang more than expected).

Fields of papers citing papers by Ming‐Ching Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Ching Chang. 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 Ming‐Ching Chang. The network helps show where Ming‐Ching Chang may publish in the future.

Co-authors

The 25 scholars most cited alongside Ming‐Ching Chang, 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 Ming‐Ching Chang Line = papers co-authored together Ming‐Ching Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 135 papers — load more, or switch the sort, to bring in the rest.

#Work
1
In Ictu Oculi: Exposing AI Created Fake Videos by Detecting Eye Blinking
Hit paper breakdown →
2018745
2
UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking
Hit paper breakdown →
2020498
3 2018195
4 2014121
5 2012110
6 2017101
7 201598
8 202078
9 201777
10 202177
11 202273
12 201870
13 201168
14 201760
15 202357
16 202457
17 202247
18 201046
19 201646
20 202344

About Ming‐Ching Chang

Ming‐Ching Chang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Industrial and Manufacturing Engineering and Media Technology, having authored 135 papers that have together received 3.7k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (35 papers), Advanced Neural Network Applications (23 papers), Human Pose and Action Recognition (13 papers), Digital Media Forensic Detection (11 papers), 3D Shape Modeling and Analysis (8 papers), Medical Image Segmentation Techniques (6 papers), Cryptography and Data Security (5 papers) and Industrial Vision Systems and Defect Detection (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.8k citations), Automotive Engineering (97 citations), Artificial Intelligence (234 citations), Radiology, Nuclear Medicine and Imaging (141 citations) and Human-Computer Interaction (42 citations). Ming‐Ching Chang has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Siwei Lyu, Yuezun Li, Honggang Qi, Longyin Wen, Zhen Lei, Lipeng Ke, Dawei Du, Jongwoo Lim, Ming–Hsuan Yang and Zhaowei Cai. Their work appears in journals such as Computer Vision and Image Understanding, IEEE Transactions on Image Processing, Journal of Applied Crystallography, IEEE Transactions on Artificial Intelligence and Scientific Reports.

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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