Xinyu Tian
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- Advanced Neural Network Applications 7
- Advanced Image and Video Retrieval Techniques 4
- Polymers and Plastics top 10%
- Conducting polymers and applications 7
- Flame retardant materials and properties 5
- Artificial Intelligence top 5%
- Wireless Signal Modulation Classification 5
- Domain Adaptation and Few-Shot Learning 4
- Signal Processing top 10%
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- Advanced Sensor and Energy Harvesting Materials 6
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- Radar Systems and Signal Processing 4
- Co-authors
- Qinghe ZhengAbdussalam ElhanashiSergio SaponaraZhiguo YuNan JiangJiahao QiuLei TaoYue Zhou
- Partner nations
- ChinaItalyUnited States
In The Last Decade
Xinyu Tian
49 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Computer Vision and Pattern Recognition 290
- Polymers and Plastics 133
- Artificial Intelligence 281
- Health Informatics 9
- Signal Processing 69
Countries citing papers authored by Xinyu Tian
This map shows the geographic impact of Xinyu Tian'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 Xinyu Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinyu Tian more than expected).
Fields of papers citing papers by Xinyu Tian
This network shows the impact of papers produced by Xinyu Tian. 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 Xinyu Tian. The network helps show where Xinyu Tian may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xinyu Tian, 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 | 2026 | 0 | |
| 2 | Rethinking the multi-scale feature hierarchy in object detection transformer (DETR)breakdown → | 2025 | 19 |
| 3 | 2025 | 1 | |
| 4 | 2024 | 15 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 6 | |
| 7 | 2024 | 29 | |
| 8 | 2024 | 11 | |
| 9 | 2024 | 13 | |
| 10 | 2024 | 6 | |
| 11 | 2023 | 37 | |
| 12 | 2023 | 58 | |
| 13 | 2023 | 58 | |
| 14 | 2022 | 9 | |
| 15 | 2022 | 34 | |
| 16 | 2021 | 4 | |
| 17 | 2020 | 132 | |
| 18 | 2020 | 18 | |
| 19 | 2020 | 7 | |
| 20 | 2019 | 84 |
About Xinyu Tian
Xinyu Tian is a scholar working on Polymers and Plastics, Computer Vision and Pattern Recognition and Software, having authored 59 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Conducting polymers and applications (7 papers), Advanced Sensor and Energy Harvesting Materials (6 papers), Wireless Signal Modulation Classification (5 papers), Flame retardant materials and properties (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Radar Systems and Signal Processing (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (290 citations), Polymers and Plastics (133 citations) and Artificial Intelligence (281 citations). Xinyu Tian has collaborated with scholars based in China, Italy and United States. Frequent co-authors include Qinghe Zheng, Abdussalam Elhanashi, Sergio Saponara, Zhiguo Yu, Nan Jiang, Jiahao Qiu, Lei Tao, Yue Zhou, Deqiang Wang and Xiaobo Cen. Their work appears in journals such as Advanced Materials, PLoS ONE and Analytical Chemistry.
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.