Jun-e Liu

33 total papers · 827 total citations
22 papers, 556 citations indexed

About

Jun-e Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Jun-e Liu has authored 22 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 4 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Jun-e Liu's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Image Segmentation Techniques (3 papers) and Advanced Neural Network Applications (3 papers). Jun-e Liu is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Image Segmentation Techniques (3 papers) and Advanced Neural Network Applications (3 papers). Jun-e Liu collaborates with scholars based in China and Singapore. Jun-e Liu's co-authors include Zhiguo Wan, Robert H. Deng, Fengping An, Rongrong Lu, Si Gao, Rui Zhang, Bingwu Liu, Xin Wang, Xiaoying Zhao and Xiaorui Zhang and has published in prestigious journals such as Information Fusion, IEEE Transactions on Information Forensics and Security and IEEE Transactions on Multimedia.

In The Last Decade

Jun-e Liu

18 papers receiving 499 citations

Hit Papers

HASBE: A Hierarchical Att... 2011 2026 2016 2021 2011 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Jun-e Liu 380 292 110 43 42 22 556
Mohamad Saraee 325 0.9× 118 0.4× 98 0.9× 30 0.7× 22 0.5× 43 505
Hamouda Chantar 334 0.9× 134 0.5× 67 0.6× 66 1.5× 48 1.1× 13 496
Minghao Zhao 318 0.8× 197 0.7× 125 1.1× 19 0.4× 98 2.3× 37 610
Yanxin Shi 267 0.7× 241 0.8× 177 1.6× 13 0.3× 69 1.6× 25 652
Ibrahim El-Henawy 388 1.0× 69 0.2× 104 0.9× 80 1.9× 48 1.1× 25 623
Waleed Alomoush 236 0.6× 91 0.3× 134 1.2× 43 1.0× 84 2.0× 34 534
Thaer Thaher 352 0.9× 161 0.6× 59 0.5× 73 1.7× 121 2.9× 26 625
Jie Wen 348 0.9× 112 0.4× 47 0.4× 21 0.5× 126 3.0× 28 529
Shaima Qureshi 214 0.6× 160 0.5× 173 1.6× 20 0.5× 64 1.5× 35 601
Kashif Javed 433 1.1× 175 0.6× 211 1.9× 27 0.6× 25 0.6× 39 631

Countries citing papers authored by Jun-e Liu

Since Specialization
Citations

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

Fields of papers citing papers by Jun-e Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun-e Liu

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