Qiang Zhai

789 total citations · 2 hit papers
13 papers, 477 citations indexed

About

Qiang Zhai is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Computer Networks and Communications. According to data from OpenAlex, Qiang Zhai has authored 13 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 3 papers in Aerospace Engineering and 2 papers in Computer Networks and Communications. Recurrent topics in Qiang Zhai's work include Advanced Image and Video Retrieval Techniques (5 papers), Visual Attention and Saliency Detection (3 papers) and Image Enhancement Techniques (3 papers). Qiang Zhai is often cited by papers focused on Advanced Image and Video Retrieval Techniques (5 papers), Visual Attention and Saliency Detection (3 papers) and Image Enhancement Techniques (3 papers). Qiang Zhai collaborates with scholars based in China, United States and Hong Kong. Qiang Zhai's co-authors include Hong Cheng, Fan Yang, Deng-Ping Fan, Xin Li, Chenglizhao Chen, Rui Huang, Ao Luo, Xin Li, Zicheng Liu and Zhicheng Jiao and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition and Remote Sensing.

In The Last Decade

Qiang Zhai

10 papers receiving 471 citations

Hit Papers

Mutual Graph Learning for Camouflaged Object Detection 2021 2026 2022 2024 2021 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qiang Zhai China 6 426 54 54 45 34 13 477
Yunqiu Lv China 7 506 1.2× 71 1.3× 56 1.0× 41 0.9× 40 1.2× 9 569
Mingchen Zhuge China 7 517 1.2× 38 0.7× 62 1.1× 68 1.5× 92 2.7× 12 602
Tengpeng Li China 6 227 0.5× 40 0.7× 25 0.5× 24 0.5× 38 1.1× 13 259
Yunzhi Zhuge China 7 304 0.7× 27 0.5× 17 0.3× 83 1.8× 46 1.4× 18 338
Fushuo Huo China 8 257 0.6× 17 0.3× 47 0.9× 47 1.0× 74 2.2× 14 326
Yanjiao Shi China 11 246 0.6× 31 0.6× 24 0.4× 51 1.1× 50 1.5× 40 320
Qi Jia China 11 475 1.1× 10 0.2× 101 1.9× 22 0.5× 74 2.2× 40 525
Dominik A. Klein Germany 8 450 1.1× 118 2.2× 51 0.9× 26 0.6× 37 1.1× 14 477
Yongjiang Luo China 8 212 0.5× 10 0.2× 37 0.7× 26 0.6× 63 1.9× 14 292

Countries citing papers authored by Qiang Zhai

Since Specialization
Citations

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

Fields of papers citing papers by Qiang Zhai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiang Zhai

This figure shows the co-authorship network connecting the top 25 collaborators of Qiang Zhai. A scholar is included among the top collaborators of Qiang Zhai 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 Qiang Zhai. Qiang Zhai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Huang, Rui, et al.. (2025). Memory-Guided Transformer with group attention for knee MRI diagnosis. Pattern Recognition. 162. 111417–111417.
2.
Yang, Fan, Xin Li, Zhicheng Jiao, et al.. (2025). SegMIC: A universal model for medical image segmentation through in-context learning. Pattern Recognition. 171. 112179–112179.
3.
Li, Xin, Fan Yang, Qiang Zhai, et al.. (2025). MExD: An Expert-Infused Diffusion Model for Whole-Slide Image Classification. 20789–20799.
4.
Zhai, Qiang, et al.. (2024). EEGGAN-Net: enhancing EEG signal classification through data augmentation. Frontiers in Human Neuroscience. 18. 1430086–1430086. 8 indexed citations
5.
Zhao, Jianwei, et al.. (2023). Co-Visual Pattern-Augmented Generative Transformer Learning for Automobile Geo-Localization. Remote Sensing. 15(9). 2221–2221. 11 indexed citations
6.
Zhai, Qiang, Fan Yang, Xin Li, et al.. (2022). Co-Communication Graph Convolutional Network for Multi-View Crowd Counting. IEEE Transactions on Multimedia. 25. 5813–5825. 6 indexed citations
7.
Zhai, Qiang, Xin Li, Fan Yang, et al.. (2022). MGL: Mutual Graph Learning for Camouflaged Object Detection. IEEE Transactions on Image Processing. 32. 1897–1910. 33 indexed citations
8.
Zhai, Qiang, Xin Li, Fan Yang, et al.. (2021). Mutual Graph Learning for Camouflaged Object Detection. 12992–13002. 213 indexed citations breakdown →
9.
Yang, Fan, Qiang Zhai, Xin Li, et al.. (2021). Uncertainty-Guided Transformer Reasoning for Camouflaged Object Detection. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 4126–4135. 195 indexed citations breakdown →
10.
Zhai, Qiang, et al.. (2020). A Survey: Artificial Intelligence and its Security in Intelligent Vehicle. 49(4). 1 indexed citations
11.
Zhai, Qiang, et al.. (2020). Learning Quintuplet Loss for Large-Scale Visual Geolocalization. IEEE Multimedia. 27(3). 34–43. 5 indexed citations
12.
Yin, Baoqun, et al.. (2018). A VCP-based Congestion Control Algorithm in Named Data Networking. 463–468. 3 indexed citations
13.
Liu, Ning, et al.. (2010). Securing Wireless Mesh Network with Mobile Firewall. 51. 1–6. 2 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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