Xinge You

6.2k total citations · 1 hit paper
148 papers, 4.2k citations indexed

About

Xinge You is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Xinge You has authored 148 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 108 papers in Computer Vision and Pattern Recognition, 42 papers in Artificial Intelligence and 27 papers in Signal Processing. Recurrent topics in Xinge You's work include Domain Adaptation and Few-Shot Learning (21 papers), Advanced Image and Video Retrieval Techniques (19 papers) and Image Retrieval and Classification Techniques (17 papers). Xinge You is often cited by papers focused on Domain Adaptation and Few-Shot Learning (21 papers), Advanced Image and Video Retrieval Techniques (19 papers) and Image Retrieval and Classification Techniques (17 papers). Xinge You collaborates with scholars based in China, Hong Kong and United States. Xinge You's co-authors include Qinmu Peng, Yantao Wei, Hong Li, Yuan Yan Tang, Yiu‐ming Cheung, Jiajia Lei, Dacheng Tao, Yuan Yuan, Weihua Ou and Xiao‐Yuan Jing and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Xinge You

144 papers receiving 4.1k citations

Hit Papers

Multiscale patch-based contrast measure for small infrare... 2016 2026 2019 2022 2016 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xinge You China 34 2.6k 951 707 676 566 148 4.2k
Elisa Ricci Italy 35 3.4k 1.3× 1.7k 1.8× 522 0.7× 398 0.6× 827 1.5× 163 5.2k
Majid Mirmehdi United Kingdom 31 2.9k 1.1× 525 0.6× 687 1.0× 233 0.3× 510 0.9× 176 4.2k
Mai Xu China 40 3.5k 1.3× 509 0.5× 674 1.0× 215 0.3× 689 1.2× 214 5.6k
Axel Pinz Austria 29 4.1k 1.5× 1.6k 1.7× 472 0.7× 944 1.4× 351 0.6× 151 5.4k
Ding Liang China 15 3.7k 1.4× 1.4k 1.5× 969 1.4× 501 0.7× 497 0.9× 39 5.5k
Alessandro Giusti Switzerland 30 2.1k 0.8× 1.6k 1.7× 299 0.4× 660 1.0× 796 1.4× 139 5.2k
Chao-Yuan Wu United States 14 3.0k 1.2× 2.1k 2.2× 537 0.8× 320 0.5× 549 1.0× 20 5.8k
Kaitao Song China 11 3.0k 1.1× 1.2k 1.2× 853 1.2× 418 0.6× 441 0.8× 27 4.5k

Countries citing papers authored by Xinge You

Since Specialization
Citations

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

Fields of papers citing papers by Xinge You

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinge You

This figure shows the co-authorship network connecting the top 25 collaborators of Xinge You. A scholar is included among the top collaborators of Xinge You based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xinge You. Xinge You is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
You, Xinge, et al.. (2025). GKA: Graph-guided knowledge association for fine-grained visual categorization. Neurocomputing. 634. 129819–129819.
2.
Chen, Shiming, Ziming Hong, Xinge You, & Ling Shao. (2025). Semantics-Conditioned Generative Zero-Shot Learning via Feature Refinement. International Journal of Computer Vision. 133(7). 4504–4521. 4 indexed citations
3.
Chen, Shiming, et al.. (2025). Adversarial Feature Training for Few-Shot Object Detection. IEEE Transactions on Circuits and Systems for Video Technology. 35(9). 9324–9336.
4.
Zou, Bin, et al.. (2024). Hybrid learning based on Fisher linear discriminant. Information Sciences. 667. 120465–120465.
5.
Miao, Zhuang, et al.. (2024). Enhancing robustness of person detection: A universal defense filter against adversarial patch attacks. Computers & Security. 146. 104066–104066. 1 indexed citations
6.
Ye, Fanghua, et al.. (2024). Concept drift adaptation with scarce labels: A novel approach based on diffusion and adversarial learning. Engineering Applications of Artificial Intelligence. 137. 109105–109105. 1 indexed citations
7.
Ma, Li, et al.. (2024). Exploring sample relationship for few-shot classification. Pattern Recognition. 159. 111089–111089. 4 indexed citations
8.
Chen, Shiming, et al.. (2024). Few-shot object detection: Research advances and challenges. Information Fusion. 107. 102307–102307. 26 indexed citations
9.
Chen, Shiming, et al.. (2024). Rethinking attribute localization for zero-shot learning. Science China Information Sciences. 67(7). 4 indexed citations
10.
Chen, Shiming, et al.. (2024). ECEA: Extensible Co-Existing Attention for Few-Shot Object Detection. IEEE Transactions on Image Processing. 33. 5564–5576. 10 indexed citations
11.
Peng, Qinmu, et al.. (2024). Detail Reinforcement Diffusion Model: Augmentation Fine-Grained Visual Categorization in Few-Shot Conditions. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(1). 630–640. 1 indexed citations
12.
Fu, Sichao, et al.. (2024). Jointly Optimized Classifiers for Few-Shot Class-Incremental Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(5). 3316–3326. 1 indexed citations
13.
Chen, Shiming, et al.. (2024). Object-Aware Image Augmentation for Audio-Visual Zero-Shot Learning. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(6). 4106–4118. 2 indexed citations
14.
Fu, Sichao, Qiong Cao, Yunwen Lei, et al.. (2023). Few-Shot Learning With Dynamic Graph Structure Preserving. IEEE Transactions on Industrial Informatics. 20(3). 3306–3315. 8 indexed citations
15.
Chen, Shiming, Ziming Hong, Guo-Sen Xie, et al.. (2022). TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(11). 1–17. 40 indexed citations
16.
Jiang, Yong, et al.. (2020). Video scene parsing: An overview of deep learning methods and datasets. Computer Vision and Image Understanding. 201. 103077–103077. 8 indexed citations
17.
Yin, Shi, Qinmu Peng, Hongming Li, et al.. (2019). Multi-instance Deep Learning with Graph Convolutional Neural Networks for Diagnosis of Kidney Diseases Using Ultrasound Imaging. Lecture notes in computer science. 11840. 146–154. 31 indexed citations
18.
Yin, Shi, Qinmu Peng, Hongming Li, et al.. (2018). Subsequent Boundary Distance Regression and Pixelwise Classification Networks for Automatic Kidney Segmentation in Ultrasound Images.. arXiv (Cornell University). 2 indexed citations
19.
Zhu, Xiaoke, Xiao‐Yuan Jing, Liang Yang, et al.. (2017). Semi-Supervised Cross-View Projection-Based Dictionary Learning for Video-Based Person Re-Identification. IEEE Transactions on Circuits and Systems for Video Technology. 28(10). 2599–2611. 29 indexed citations
20.
You, Xinge & Yuan Yan Tang. (2007). Wavelet-Based Approach to Character Skeleton. IEEE Transactions on Image Processing. 16(5). 1220–1231. 44 indexed citations

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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