Cong Yao

17.0k total citations · 6 hit papers
79 papers, 6.4k citations indexed

About

Cong Yao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Cong Yao has authored 79 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 10 papers in Media Technology. Recurrent topics in Cong Yao's work include Handwritten Text Recognition Techniques (35 papers), Image Retrieval and Classification Techniques (18 papers) and Advanced Image and Video Retrieval Techniques (17 papers). Cong Yao is often cited by papers focused on Handwritten Text Recognition Techniques (35 papers), Image Retrieval and Classification Techniques (18 papers) and Advanced Image and Video Retrieval Techniques (17 papers). Cong Yao collaborates with scholars based in China, United States and India. Cong Yao's co-authors include Xiang Bai, Baoguang Shi, Wenyu Liu, Pengyuan Lyu, Xinggang Wang, Minghui Liao, Zhaoyi Wan, Zhuowen Tu, Xiang Bai and Yi Ma and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Cong Yao

71 papers receiving 6.2k citations

Hit Papers

An End-to-End Trainable Neural Network for Image-Based Se... 2012 2026 2016 2021 2016 2012 2018 2020 2016 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cong Yao China 28 5.6k 2.3k 1.2k 237 210 79 6.4k
Yi Xu China 35 3.2k 0.6× 834 0.4× 901 0.7× 251 1.1× 226 1.1× 188 5.2k
Dapeng Tao China 45 3.8k 0.7× 884 0.4× 1.2k 1.0× 300 1.3× 124 0.6× 198 5.0k
Meng Yang China 29 4.6k 0.8× 1.2k 0.5× 1.3k 1.1× 1.1k 4.6× 128 0.6× 123 5.8k
Fei Yin China 28 3.1k 0.6× 1.1k 0.5× 1.4k 1.1× 167 0.7× 77 0.4× 140 3.9k
Yuming Fang China 45 6.9k 1.2× 2.7k 1.2× 512 0.4× 224 0.9× 42 0.2× 272 7.6k
Xiaoyang Tan China 21 3.6k 0.6× 717 0.3× 626 0.5× 760 3.2× 84 0.4× 79 4.5k
Changqing Zhang China 46 5.3k 1.0× 1.3k 0.6× 3.4k 2.8× 323 1.4× 255 1.2× 101 7.5k
Xu-Yao Zhang China 27 2.4k 0.4× 802 0.3× 1.5k 1.3× 168 0.7× 96 0.5× 115 3.4k
Dong Huang China 38 2.7k 0.5× 445 0.2× 2.2k 1.8× 275 1.2× 246 1.2× 175 4.6k
Thomas Deselaers Germany 27 3.1k 0.6× 418 0.2× 988 0.8× 237 1.0× 104 0.5× 64 3.9k

Countries citing papers authored by Cong Yao

Since Specialization
Citations

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

Fields of papers citing papers by Cong Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cong Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Cong Yao. A scholar is included among the top collaborators of Cong Yao 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 Cong Yao. Cong Yao 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
2.
Yao, Cong, Lin An, Ang-Xin Song, et al.. (2025). Classification and identification of chicken-derived adulteration in pork patties: A multi-dimensional quality profile and machine learning-based approach. Food Control. 176. 111381–111381. 4 indexed citations
4.
Zhu, Yuanzhi, Dezhi Peng, Zhenhua Yang, et al.. (2024). HierCode: A lightweight hierarchical codebook for zero-shot Chinese text recognition. Pattern Recognition. 158. 110963–110963. 6 indexed citations
5.
Gao, Feiyu, et al.. (2024). DocHieNet: A Large and Diverse Dataset for Document Hierarchy Parsing. 1129–1142. 1 indexed citations
6.
Yang, Zhibo, et al.. (2024). VL-Reader: Vision and Language Reconstructor is an Effective Scene Text Recognizer. 4207–4216. 1 indexed citations
7.
Zheng, Qi, et al.. (2024). LayoutLLM: Layout Instruction Tuning with Large Language Models for Document Understanding. 15630–15640. 12 indexed citations
9.
Li, Meijuan, et al.. (2023). Gender differences and clinical correlates in the age of the first hospitalization in patients with drug-naïve schizophrenia in China: a cross-sectional study. European Archives of Psychiatry and Clinical Neuroscience. 274(6). 1417–1426. 1 indexed citations
10.
Wang, Shuo, Xue Zhang, Cong Yao, et al.. (2023). Prevalence and influencing factors of sleep disturbance among medical students under the COVID-19 pandemic. European Archives of Psychiatry and Clinical Neuroscience. 275(1). 89–98. 3 indexed citations
11.
Yao, Cong, Yun Fu, Yanzhe Li, et al.. (2023). Sex- and age-specific prevalence and risk factors of depressive symptoms in Parkinson’s disease. Journal of Neural Transmission. 130(10). 1291–1302. 3 indexed citations
12.
Liao, Minghui, et al.. (2022). Real-Time Scene Text Detection With Differentiable Binarization and Adaptive Scale Fusion. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(1). 919–931. 181 indexed citations breakdown →
13.
Cao, Haiyan, Yongjie Zhou, Tao Li, et al.. (2021). The Prevalence, Risk Factors and Clinical Correlates of QTc Prolongation in Chinese Hospitalized Patients With Chronic Schizophrenia. Frontiers in Psychiatry. 12. 704045–704045. 10 indexed citations
14.
Wan, Zhaoyi, et al.. (2020). On Vocabulary Reliance in Scene Text Recognition. 11422–11431. 36 indexed citations
15.
Long, Shangbang, et al.. (2019). Alchemy: Techniques for Rectification Based Irregular Scene Text Recognition. arXiv (Cornell University). 1 indexed citations
16.
Yao, Cong, Xin Zhang, Xiang Bai, et al.. (2013). Rotation-Invariant Features for Multi-Oriented Text Detection in Natural Images. PLoS ONE. 8(8). e70173–e70173. 22 indexed citations
17.
Yao, Cong. (2009). Classification of Chinese Red Wines by Using an E-Tongue. Chuangan jishu xuebao.
18.
Yao, Cong, et al.. (2006). Probabilistic Atlas-guided Eigen-organ Method for Simultaneous Bounding Box Estimation of Multiple Organs in Volumetric CT Images. 24(3). 191–200. 2 indexed citations
19.
Yao, Cong, et al.. (2006). Simultaneous location detection of multi-organ by atlas-guided eigen-organ method in volumetric medical images. International Journal of Computer Assisted Radiology and Surgery. 1. 42–45. 11 indexed citations
20.
Yao, Cong, et al.. (2005). Proposal of Atlas-guided Eigen-organ Method for Location Detection of Multi-Organs in Three Dimensional Medical Images(Joint Session 2). 105(303). 97–102. 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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