Xinneng Yang
Impact in
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- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Medical Image Segmentation Techniques
- Media Technology top 5%
- Remote-Sensing Image Classification
Papers in
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- Advanced Neural Network Applications 4
- Advanced Image and Video Retrieval Techniques 2
- Multimodal Machine Learning Applications 1
- Robotic Path Planning Algorithms 1
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- Autonomous Vehicle Technology and Safety 2
- Vehicle Dynamics and Control Systems 1
- Co-authors
- Feilin Liu (4 shared papers)Yan Wu (5 shared papers)Yujun Liao (3 shared papers)Yujian Mo (3 shared papers)Junqiao Zhao (3 shared papers)Chen Ye (1 shared paper)
- Journals
- Neurocomputing (1 paper)Pattern Analysis and Applications (1 paper)International Journal of Pattern Recognition and Artificial Intelligence (1 paper)
- Partner nations
- China
In The Last Decade
Xinneng Yang
4 papers receiving 420 citations
Xinneng Yang's Hit Papers
Peers
Comparison fields: 5 of 91
- Computer Vision and Pattern Recognition 222
- Media Technology 67
- Industrial and Manufacturing Engineering 42
- Geology 21
- Artificial Intelligence 101
Countries citing papers authored by Xinneng Yang
This map shows the geographic impact of Xinneng 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 Xinneng Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinneng Yang more than expected).
Fields of papers citing papers by Xinneng Yang
This network shows the impact of papers produced by Xinneng 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 Xinneng Yang. The network helps show where Xinneng Yang may publish in the future.
Co-authors
The 6 scholars most cited alongside Xinneng Yang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Review the state-of-the-art technologies of semantic segmentation based on deep learning Hit paper breakdown → | 2022 | 416 |
| 2 | 2022 | 9 | |
| 3 | 2021 | 3 | |
| 4 | 2022 | 1 | |
| 5 | 2022 | 0 |
About Xinneng Yang
Xinneng Yang is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering, Artificial Intelligence, Civil and Structural Engineering and Infectious Diseases, having authored 5 papers that have together received 429 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), Advanced Image and Video Retrieval Techniques (2 papers), Autonomous Vehicle Technology and Safety (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Multimodal Machine Learning Applications (1 paper), Vehicle Dynamics and Control Systems (1 paper), Infrastructure Maintenance and Monitoring (1 paper) and Robotic Path Planning Algorithms (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (222 citations), Media Technology (67 citations), Industrial and Manufacturing Engineering (42 citations), Geology (21 citations) and Artificial Intelligence (101 citations). Xinneng Yang has collaborated with scholars based in China. Frequent co-authors include Feilin Liu, Yan Wu, Yujun Liao, Yujian Mo, Junqiao Zhao and Chen Ye. Their work appears in journals such as Neurocomputing, Pattern Analysis and Applications and International Journal of Pattern Recognition and 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.