Du‐Ming Tsai

6.1k total citations
113 papers, 4.7k citations indexed

About

Du‐Ming Tsai is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Computational Mechanics. According to data from OpenAlex, Du‐Ming Tsai has authored 113 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Computer Vision and Pattern Recognition, 75 papers in Industrial and Manufacturing Engineering and 27 papers in Computational Mechanics. Recurrent topics in Du‐Ming Tsai's work include Industrial Vision Systems and Defect Detection (73 papers), Image and Object Detection Techniques (41 papers) and Surface Roughness and Optical Measurements (26 papers). Du‐Ming Tsai is often cited by papers focused on Industrial Vision Systems and Defect Detection (73 papers), Image and Object Detection Techniques (41 papers) and Surface Roughness and Optical Measurements (26 papers). Du‐Ming Tsai collaborates with scholars based in Taiwan, China and Singapore. Du‐Ming Tsai's co-authors include Shin-Min Chao, Chi-Jie Lu, Wei‐Yao Chiu, Shu‐Kai S. Fan, Wei-Chen Li, Shih-Chieh Wu, Bo Hsiao, Weichen Li, Ya‐Hui Tsai and Jeng-Fung Chen and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition and Solar Energy Materials and Solar Cells.

In The Last Decade

Du‐Ming Tsai

111 papers receiving 4.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Du‐Ming Tsai Taiwan 41 2.5k 2.5k 1.1k 881 644 113 4.7k
G.K.H. Pang Hong Kong 30 1.7k 0.7× 2.2k 0.9× 1.2k 1.1× 751 0.9× 833 1.3× 150 3.9k
De Xu China 32 2.2k 0.9× 1.1k 0.5× 450 0.4× 251 0.3× 432 0.7× 269 4.3k
Dongwei Ren China 19 3.6k 1.4× 676 0.3× 1.0k 0.9× 126 0.1× 307 0.5× 49 5.2k
Yanlong Cao China 24 829 0.3× 617 0.2× 415 0.4× 234 0.3× 211 0.3× 117 2.2k
Chunjing Xu China 23 4.4k 1.7× 538 0.2× 1.2k 1.1× 160 0.2× 386 0.6× 63 6.3k
Kai Han China 21 3.1k 1.2× 537 0.2× 652 0.6× 105 0.1× 351 0.5× 48 5.0k
Jonathan Masci Switzerland 15 1.9k 0.8× 311 0.1× 372 0.3× 549 0.6× 260 0.4× 26 3.8k
Hua Yang China 24 750 0.3× 558 0.2× 253 0.2× 309 0.4× 341 0.5× 147 2.1k
Kristin Dana United States 30 2.8k 1.1× 236 0.1× 452 0.4× 555 0.6× 393 0.6× 76 4.5k

Countries citing papers authored by Du‐Ming Tsai

Since Specialization
Citations

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

Fields of papers citing papers by Du‐Ming Tsai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Du‐Ming Tsai

This figure shows the co-authorship network connecting the top 25 collaborators of Du‐Ming Tsai. A scholar is included among the top collaborators of Du‐Ming Tsai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Du‐Ming Tsai. Du‐Ming Tsai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Fan, Shu‐Kai S., et al.. (2023). Self-Assured Deep Learning With Minimum Pre-Labeled Data for Wafer Pattern Classification. IEEE Transactions on Semiconductor Manufacturing. 36(3). 404–415. 6 indexed citations
2.
Fan, Shu‐Kai S., et al.. (2023). Effective Variational-Autoencoder-Based Generative Models for Highly Imbalanced Fault Detection Data in Semiconductor Manufacturing. IEEE Transactions on Semiconductor Manufacturing. 36(2). 205–214. 25 indexed citations
3.
Fan, Shu‐Kai S., et al.. (2022). Key Feature Identification for Monitoring Wafer-to-Wafer Variation in Semiconductor Manufacturing. IEEE Transactions on Automation Science and Engineering. 19(3). 1530–1541. 16 indexed citations
4.
Fan, Shu‐Kai S., et al.. (2021). Fault Diagnosis of Wafer Acceptance Test and Chip Probing Between Front-End-of-Line and Back-End-of-Line Processes. IEEE Transactions on Automation Science and Engineering. 19(4). 3068–3082. 34 indexed citations
5.
Tsai, Du‐Ming, et al.. (2021). Auto-Annotated Deep Segmentation for Surface Defect Detection. IEEE Transactions on Instrumentation and Measurement. 70. 1–10. 64 indexed citations
6.
Fan, Shu‐Kai S., et al.. (2021). Data Visualization of Anomaly Detection in Semiconductor Processing Tools. IEEE Transactions on Semiconductor Manufacturing. 35(2). 186–197. 8 indexed citations
7.
Tsai, Du‐Ming, et al.. (2021). Autoencoder-based anomaly detection for surface defect inspection. Advanced Engineering Informatics. 48. 101272–101272. 82 indexed citations
8.
Tsai, Du‐Ming, et al.. (2021). Deep learning from imbalanced data for automatic defect detection in multicrystalline solar wafer images. Measurement Science and Technology. 32(12). 124003–124003. 9 indexed citations
9.
Fan, Shu‐Kai S., et al.. (2020). Data-Driven Approach for Fault Detection and Diagnostic in Semiconductor Manufacturing. IEEE Transactions on Automation Science and Engineering. 17(4). 1925–1936. 121 indexed citations
10.
Tsai, Du‐Ming, et al.. (2019). Fast and Precise Positioning in PCBs Using Deep Neural Network Regression. IEEE Transactions on Instrumentation and Measurement. 69(7). 4692–4701. 30 indexed citations
11.
Fan, Shu‐Kai S., et al.. (2019). Key Parameter Identification and Defective Wafer Detection of Semiconductor Manufacturing Processes Using Image Processing Techniques. IEEE Transactions on Semiconductor Manufacturing. 32(4). 544–552. 22 indexed citations
12.
13.
Tsai, Du‐Ming, et al.. (2018). Defect Inspection of Liquid-Crystal-Display (LCD) Panels in Repetitive Pattern Images Using 2D Fourier Image Reconstruction. 13–18. 2 indexed citations
14.
Tsai, Du‐Ming, et al.. (2017). Machine Vision-Based Positioning and Inspection Using Expectation–Maximization Technique. IEEE Transactions on Instrumentation and Measurement. 66(11). 2858–2868. 63 indexed citations
15.
Tsai, Du‐Ming, et al.. (2015). Moving object detection from a mobile robot using basis image matching. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 1–10. 1 indexed citations
16.
Tsai, Du‐Ming & Wei‐Yao Chiu. (2013). A real-time ICA-based activity recognition in video sequences. Machine Vision and Applications. 467–470. 1 indexed citations
17.
Tsai, Du‐Ming, et al.. (2008). Non-referential, self-compared shape defect inspection for bond pads with deformed shapes. International Journal of Production Research. 47(5). 1225–1244. 5 indexed citations
18.
Tsai, Du‐Ming & Shin-Min Chao. (2004). An anisotropic diffusion-based defect detection for sputtered surfaces with inhomogeneous textures. Image and Vision Computing. 23(3). 325–338. 20 indexed citations
19.
Tsai, Du‐Ming, et al.. (1998). A moment-preserving approach for depth from defocus. Pattern Recognition. 31(5). 551–560. 10 indexed citations
20.
Tsai, Du‐Ming, et al.. (1996). A fast machine vision approach for automatic recognition of industrial parts. International Journal of Production Research. 34(3). 687–699. 2 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by G.K.H. Pang Breakdown of academic impact, for papers by De Xu Breakdown of academic impact, for papers by Dongwei Ren Breakdown of academic impact, for papers by Yanlong Cao Breakdown of academic impact, for papers by Chunjing Xu Breakdown of academic impact, for papers by Kai Han Breakdown of academic impact, for papers by Jonathan Masci Breakdown of academic impact, for papers by Hua Yang Breakdown of academic impact, for papers by Kristin Dana
Rankless by CCL
2026