Ting-Wu Chin

About

Ting-Wu Chin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Ting-Wu Chin has authored 12 papers receiving a total of 244 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 4 papers in Electrical and Electronic Engineering. Recurrent topics in Ting-Wu Chin’s work include Advanced Neural Network Applications (9 papers), Domain Adaptation and Few-Shot Learning (7 papers) and CCD and CMOS Imaging Sensors (3 papers). Ting-Wu Chin is often cited by papers focused on Advanced Neural Network Applications (9 papers), Domain Adaptation and Few-Shot Learning (7 papers) and CCD and CMOS Imaging Sensors (3 papers). Ting-Wu Chin collaborates with scholars based in United States, Taiwan and Israel. Ting-Wu Chin's co-authors include Diana Marculescu, Ruizhou Ding, Cha Zhang, Hasan Genc, Matthew Halpern, Vijay Janapa Reddi, Dimitrios Stamoulis, Zhuo Chen, Anand Prakash and Shiao‐Li Tsao and has published in prestigious journals such as IEEE Micro, ACM Transactions on Embedded Computing Systems and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Co-authorship network of co-authors of Ting-Wu Chin i

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Fields of papers citing papers by Ting-Wu Chin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ting-Wu Chin. 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 Ting-Wu Chin. The network helps show where Ting-Wu Chin may publish in the future.

Countries citing papers authored by Ting-Wu Chin

Since Specialization

Citations

This map shows the geographic impact of Ting-Wu Chin'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 Ting-Wu Chin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ting-Wu Chin more than expected).

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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