Anwen Hu

642 citations
17 papers · 143 indexed · h-index 7
Journals
Wuhan Daxue xuebao. Xinxi kexue ban (1 paper)arXiv (Cornell University) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (3 papers)
Partner nations
ChinaFranceUnited States

In The Last Decade

Anwen Hu

13 papers receiving 140 citations

Peers

Anwen Hu
Comparison fields: 5 of 35
  • Computer Vision and Pattern Recognition 83
  • Artificial Intelligence 82
  • Media Technology 7
  • Signal Processing 4
  • Information Systems 7
Replace Ju Xu with:
Ju Xu China
Orestis Plevrakis United States
Andrew Drozdov United States
Nikolay Bogoychev United Kingdom
Daniel Stökl Ben Ezra France
Dominique Stutzmann France
Jeffrey Ling United States
Barun Patra United States
Chenggang Zhao China
Ke Tran Netherlands
Anwen Hu relative to Ju Xu China Ju Xu's profile →
Citations per field
00.5×7.8×
Ju Xu · 1×
Citations per year

Countries citing papers authored by Anwen Hu

Since Specialization
Citations

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

Fields of papers citing papers by Anwen Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Anwen Hu, 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 Anwen Hu Line = papers co-authored together Anwen Hu links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 20252
2 20246
3 202444
4 202412
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11 20230
12 20230
13 20220
14 20216
15 202010
16 202021
17
Discussion on "Strict Geometric Model Based on Affine Transformation for Remote Sensing Image with High Resolution"
20060

About Anwen Hu

Anwen Hu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Hardware and Architecture, having authored 17 papers that have together received 143 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (10 papers), Topic Modeling (7 papers), Natural Language Processing Techniques (7 papers), Advanced Image and Video Retrieval Techniques (4 papers), Video Analysis and Summarization (3 papers), Human Pose and Action Recognition (3 papers), Handwritten Text Recognition Techniques (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (83 citations), Artificial Intelligence (82 citations) and Media Technology (7 citations). Anwen Hu has collaborated with scholars based in China, France and United States. Frequent co-authors include Qin Jin, Jiabo Ye, Qinghao Ye, Ming Yan, Haiyang Xu, Fei Huang, Shizhe Chen, Jian‐Yun Nie, Haowei Liu and Ji Zhang. Their work appears in journals such as Wuhan Daxue xuebao. Xinxi kexue ban, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

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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