Hangfan Liu

838 total citations
40 papers, 588 citations indexed

About

Hangfan Liu is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computational Mechanics. According to data from OpenAlex, Hangfan Liu has authored 40 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 11 papers in Media Technology and 9 papers in Computational Mechanics. Recurrent topics in Hangfan Liu's work include Image and Signal Denoising Methods (17 papers), Advanced Image Processing Techniques (14 papers) and Sparse and Compressive Sensing Techniques (9 papers). Hangfan Liu is often cited by papers focused on Image and Signal Denoising Methods (17 papers), Advanced Image Processing Techniques (14 papers) and Sparse and Compressive Sensing Techniques (9 papers). Hangfan Liu collaborates with scholars based in China, United States and Singapore. Hangfan Liu's co-authors include Ruiqin Xiong, Wen Gao, Siwei Ma, Jian Zhang, Xinfeng Zhang, Feng Wu, Xiaopeng Fan, Yongbing Zhang, Tiejun Huang and Wen Gao and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Image Processing.

In The Last Decade

Hangfan Liu

39 papers receiving 576 citations

Peers

Hangfan Liu
Comparison fields: 5 of 73
  • Computer Vision and Pattern Recognition 328
  • Media Technology 157
  • Computational Mechanics 112
  • Radiology, Nuclear Medicine and Imaging 90
  • Biomedical Engineering 75
Replace Hojjat Seyed Mousavi with:
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Chaoyi Zhang Australia
Dongyue Chen China
Sim‐Heng Ong Singapore
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Lei Du China
Yonggang Shi China
Hojjat Seyed Mousavi United States View profile →
Citations per field, relative to Hangfan Liu
Hangfan Liu · 1×
Citations per year, relative to Hangfan Liu
Hangfan Liu · 1×

Countries citing papers authored by Hangfan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Hangfan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hangfan Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Hangfan Liu. A scholar is included among the top collaborators of Hangfan 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 Hangfan Liu. Hangfan Liu 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
# Work Indexed citations
1 5
2 3
3 1
4 13
5 10
6 17
7 0
8 13
9 3
10 2
11
DeepSEED: 3D Squeeze-and-Excitation Encoder-Decoder ConvNets for Pulmonary Nodule Detection.
4
12 31
13 8
14 16
15 8
16 14
17 5
18 7
19 10
20 46

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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