Hangjun Che

1.9k citations
73 papers · 1.3k · 2 hit papers · h-index 23

Impact in

Papers in

Hangjun Che

62 papers receiving 1.2k citations

Hangjun Che's Hit Papers

Projected cross-view learning for unbalanced incomplete multi-view clustering 2024 · 53 citations
530+1+2Years since publication255075

Peers

Hangjun Che
Comparison fields: 5 of 91
  • Computational Mathematics 87
  • Computer Vision and Pattern Recognition 509
  • Artificial Intelligence 585
  • Urban Studies 61
  • Signal Processing 94
Replace Ye Yuan with:
Ye Yuan China
Yan Pan China
Yi-Dong Shen China
Dexian Wang China
Dafang Zhang China
Xiangfeng Wang China
Paolo Di Lorenzo Italy
Guorui Feng China
Hangjun Che relative to Ye Yuan China Ye Yuan's profile →
Citations per field
00.5×
Ye Yuan · 1×
Citations per year

Countries citing papers authored by Hangjun Che

Since Specialization
Citations

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

Fields of papers citing papers by Hangjun Che

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hangjun Che, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hangjun Che Line = papers co-authored together Hangjun Che links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019110
2 202086
3
Robust multi-view non-negative matrix factorization with adaptive graph and diversity constraints
Hit paper breakdown →
202382
4 201866
5
Projected cross-view learning for unbalanced incomplete multi-view clustering
Hit paper breakdown →
202453
6 201850
7 202346
8 202341
9 202437
10 202336
11 201935
12 202335
13 202135
14 201432
15 202431
16 202230
17 202229
18 202229
19 202328
20 202227

About Hangjun Che

Hangjun Che is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Urban Studies and Computational Mathematics, having authored 73 papers that have together received 1.3k indexed citations. Recurring topics across this work include Face and Expression Recognition (28 papers), Neural Networks and Applications (14 papers), Sparse and Compressive Sensing Techniques (13 papers), Tensor decomposition and applications (8 papers), Advanced Computing and Algorithms (8 papers), Image Retrieval and Classification Techniques (7 papers), Machine Learning and ELM (5 papers) and Advanced Clustering Algorithms Research (5 papers). The work is most often cited by research in Computational Mathematics (87 citations), Computer Vision and Pattern Recognition (509 citations), Artificial Intelligence (585 citations), Urban Studies (61 citations) and Signal Processing (94 citations). Hangjun Che has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Jun Wang, Man-Fai Leung, Cheng Liu, Chuandong Li, Xing He, Tingwen Huang, Shiping Wen, Chenglu Li, Yan Zheng and Zheng Yan. Their work appears in journals such as Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Consumer Electronics, Information Fusion and Neurocomputing.

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.

Explore authors with similar magnitude of impact