Bang Yang

410 citations
15 papers · 221 · h-index 7

Impact in

Papers in

    • Multimodal Machine Learning Applications 9
    • Video Analysis and Summarization 6
    • Human Pose and Action Recognition 5
    • Advanced Image and Video Retrieval Techniques 3
    • Topic Modeling 4
    • Natural Language Processing Techniques 2
    • Domain Adaptation and Few-Shot Learning 2

Bang Yang

14 papers receiving 218 citations

Peers

Bang Yang
Comparison fields: 5 of 49
  • Health Informatics 26
  • Computer Vision and Pattern Recognition 119
  • Artificial Intelligence 74
  • Radiology, Nuclear Medicine and Imaging 22
  • Signal Processing 8
Replace Chaofan Tao with:
Chaofan Tao Hong Kong
Weidi Xie China
Maximilian Ilse Netherlands
Olivia Wiles United Kingdom
Yuxuan Sun China
Bosheng Qin China
Yuchen Zhuang United States
Raul Puri United States
Robik Shrestha United States
Bang Yang relative to Chaofan Tao Hong Kong Chaofan Tao's profile →
Citations per field
00.5×1.5×2.1×
Chaofan Tao · 1×
Citations per year

Countries citing papers authored by Bang Yang

Since Specialization
Citations

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

Fields of papers citing papers by Bang Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 202382
2 202154
3 202319
4 202119
5 20229
6 20258
7 20247
8 20245
9 20075
10 20255
11 20233
12
Non-Autoregressive Video Captioning with Iterative Refinement
20193
13 20221
14 20211
15 20240

About Bang Yang

Bang Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Molecular Biology, Information Systems and Health Informatics, having authored 15 papers that have together received 221 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Video Analysis and Summarization (6 papers), Human Pose and Action Recognition (5 papers), Topic Modeling (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Natural Language Processing Techniques (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Hand Gesture Recognition Systems (1 paper). The work is most often cited by research in Health Informatics (26 citations), Computer Vision and Pattern Recognition (119 citations), Artificial Intelligence (74 citations), Radiology, Nuclear Medicine and Imaging (22 citations) and Signal Processing (8 citations). Bang Yang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yuexian Zou, Fenglin Liu, Can Zhang, Xian Wu, David A. Clifton, Lei Clifton, Yefeng Zheng, Chenyu You, Meng Cao and Tingting Zhu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, npj Digital Medicine, IEEE Access, Food Chemistry and IEEE Transactions on Image Processing.

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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