Deyin Liu

64 total papers · 639 total citations
33 papers, 425 citations indexed

About

Deyin Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Surgery. According to data from OpenAlex, Deyin Liu has authored 33 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 5 papers in Surgery. Recurrent topics in Deyin Liu's work include Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Neural Network Applications (4 papers). Deyin Liu is often cited by papers focused on Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Neural Network Applications (4 papers). Deyin Liu collaborates with scholars based in China, Australia and United Kingdom. Deyin Liu's co-authors include Lin Wu, Lin Qi, Farid Boussaïd, Qing Ling, Mohammed Bennamoun, Xu Chen, Zhi Zhou, Yibin Meng, Richang Hong and Jialie Shen and has published in prestigious journals such as Scientific Reports, Biochemical and Biophysical Research Communications and IEEE Transactions on Image Processing.

In The Last Decade

Deyin Liu

28 papers receiving 420 citations

Author Peers

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

Author						Papers	Cites
Deyin Liu	216	107	61	51	50	33	425
Aiping Huang	122 0.6×	105 1.0×	93 1.5×	29 0.6×	30 0.6×	41	477
Praveen Kaushik	89 0.4×	54 0.5×	39 0.6×	86 1.7×	79 1.6×	20	429
Zhiyi Lin	86 0.4×	200 1.9×	128 2.1×	22 0.4×	104 2.1×	39	492
Lei You	135 0.6×	112 1.0×	129 2.1×	38 0.7×	29 0.6×	23	454
Dhirendra Pratap Singh	98 0.5×	93 0.9×	51 0.8×	36 0.7×	21 0.4×	62	449
Harshvardhan GM	96 0.4×	161 1.5×	32 0.5×	28 0.5×	9 0.2×	20	476
Tao Yang	219 1.0×	52 0.5×	45 0.7×	15 0.3×	41 0.8×	18	440
R.C. Mann	113 0.5×	127 1.2×	64 1.0×	22 0.4×	9 0.2×	27	368
Seyyed Mohammad Razavi	82 0.4×	102 1.0×	62 1.0×	23 0.5×	19 0.4×	30	438
Junsheng Zhou	188 0.9×	132 1.2×	26 0.4×	17 0.3×	17 0.3×	53	481

Countries citing papers authored by Deyin Liu

Since Specialization

Citations

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

Fields of papers citing papers by Deyin Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Deyin Liu. 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 Deyin Liu. The network helps show where Deyin Liu may publish in the future.

Co-authorship network of co-authors of Deyin Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Deyin Liu. A scholar is included among the top collaborators of Deyin Liu 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 Deyin Liu. Deyin Liu 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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