Xiangyu Yue
- Geology top 1%
-
- Multimodal Machine Learning Applications 10
- Advanced Neural Network Applications 8
- Generative Adversarial Networks and Image Synthesis 3
- Environmental Engineering top 2%
- Artificial Intelligence top 1%
- Domain Adaptation and Few-Shot Learning 11
- Topic Modeling 4
- Anomaly Detection Techniques and Applications 4
- Adversarial Robustness in Machine Learning 3
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- COVID-19 diagnosis using AI 3
- Co-authors
- Kurt KeutzerSicheng ZhaoBoRui WuAlberto Sangiovanni‐VincentelliBoqing GongXuanyu ZhouSanjit A. SeshiaPhilip David
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)International Journal of Computer Vision (1 paper)IEEE Transactions on Cybernetics (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Xiangyu Yue
31 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Geology 405
- Computer Vision and Pattern Recognition 1.3k
- Environmental Engineering 534
- Computer Graphics and Computer-Aided Design 102
- Artificial Intelligence 849
Countries citing papers authored by Xiangyu Yue
This map shows the geographic impact of Xiangyu Yue'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 Xiangyu Yue with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiangyu Yue more than expected).
Fields of papers citing papers by Xiangyu Yue
This network shows the impact of papers produced by Xiangyu Yue. 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 Xiangyu Yue. The network helps show where Xiangyu Yue may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiangyu Yue, 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 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 1 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 2 | |
| 7 | 2024 | 26 | |
| 8 | UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognitionbreakdown → | 2024 | 134 |
| 9 | 2024 | 1 | |
| 10 | 2024 | 1 | |
| 11 | 2021 | 15 | |
| 12 | 2021 | 9 | |
| 13 | 2021 | 108 | |
| 14 | 2021 | 15 | |
| 15 | PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentationbreakdown → | 2020 | 361 |
| 16 | SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloudbreakdown → | 2019 | 457 |
| 17 | 2019 | 242 | |
| 18 | Scenic: Language-Based Scene Generation. | 2018 | 7 |
| 19 | 2018 | 219 | |
| 20 | 2018 | 134 |
About Xiangyu Yue
Xiangyu Yue is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Instrumentation, having authored 36 papers that have together received 2.4k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (11 papers), Multimodal Machine Learning Applications (10 papers), Advanced Neural Network Applications (8 papers), Topic Modeling (4 papers), Anomaly Detection Techniques and Applications (4 papers), COVID-19 diagnosis using AI (3 papers), Generative Adversarial Networks and Image Synthesis (3 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Geology (405 citations), Computer Vision and Pattern Recognition (1.3k citations) and Environmental Engineering (534 citations). Xiangyu Yue has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Kurt Keutzer, Sicheng Zhao, BoRui Wu, Alberto Sangiovanni‐Vincentelli, Boqing Gong, Xuanyu Zhou, Sanjit A. Seshia, Philip David, Hassan Foroosh and Yang Zhang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Cybernetics.
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.