Yi‐Ta Wu

48 total papers · 807 total citations
29 papers, 518 citations indexed

About

Yi‐Ta Wu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Yi‐Ta Wu has authored 29 papers receiving a total of 518 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Yi‐Ta Wu's work include AI in cancer detection (6 papers), Advanced Steganography and Watermarking Techniques (6 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Yi‐Ta Wu is often cited by papers focused on AI in cancer detection (6 papers), Advanced Steganography and Watermarking Techniques (6 papers) and Advanced Image and Video Retrieval Techniques (6 papers). Yi‐Ta Wu collaborates with scholars based in United States and Taiwan. Yi‐Ta Wu's co-authors include Frank Y. Shih, Jiazheng Shi, Jun Wei, Heang‐Ping Chan, Berkman Sahiner, Lubomir M. Hadjiiski, Chuan Zhou, Mark A. Helvie, James Geller and Jun Ge and has published in prestigious journals such as Pattern Recognition, Medical Physics and Computer Vision and Image Understanding.

In The Last Decade

Yi‐Ta Wu

26 papers receiving 474 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Yi‐Ta Wu	341	174	124	68	41	29	518
Qingyao Wu	161 0.5×	176 1.0×	182 1.5×	63 0.9×	24 0.6×	38	594
Mengjia Xu	164 0.5×	176 1.0×	70 0.6×	30 0.4×	20 0.5×	26	532
Po-Whei Huang	293 0.9×	264 1.5×	110 0.9×	31 0.5×	14 0.3×	17	507
Anne C. Elster	192 0.6×	94 0.5×	87 0.7×	40 0.6×	54 1.3×	50	496
Phen-Lan Lin	237 0.7×	116 0.7×	61 0.5×	31 0.5×	68 1.7×	30	475
Yadunath Pathak	131 0.4×	290 1.7×	325 2.6×	43 0.6×	35 0.9×	19	609
Rushil Anirudh	165 0.5×	148 0.9×	115 0.9×	56 0.8×	34 0.8×	52	485
Earl E. Gose	133 0.4×	183 1.1×	73 0.6×	23 0.3×	16 0.4×	24	456
R. Lojacono	229 0.7×	268 1.5×	90 0.7×	17 0.3×	55 1.3×	51	456
Dhirendra Pratap Singh	98 0.3×	93 0.5×	75 0.6×	65 1.0×	36 0.9×	62	449

Countries citing papers authored by Yi‐Ta Wu

Since Specialization

Citations

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

Fields of papers citing papers by Yi‐Ta Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi‐Ta Wu. 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 Yi‐Ta Wu. The network helps show where Yi‐Ta Wu may publish in the future.

Co-authorship network of co-authors of Yi‐Ta Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Yi‐Ta Wu. A scholar is included among the top collaborators of Yi‐Ta Wu 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 Yi‐Ta Wu. Yi‐Ta Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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