Zhi Tang

3.6k total citations · 1 hit paper
131 papers, 2.1k citations indexed

About

Zhi Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Zhi Tang has authored 131 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Computer Vision and Pattern Recognition, 45 papers in Artificial Intelligence and 30 papers in Computational Theory and Mathematics. Recurrent topics in Zhi Tang's work include Handwritten Text Recognition Techniques (47 papers), Advanced Image and Video Retrieval Techniques (30 papers) and Image Retrieval and Classification Techniques (29 papers). Zhi Tang is often cited by papers focused on Handwritten Text Recognition Techniques (47 papers), Advanced Image and Video Retrieval Techniques (30 papers) and Image Retrieval and Classification Techniques (29 papers). Zhi Tang collaborates with scholars based in China, United States and Singapore. Zhi Tang's co-authors include Yongtao Wang, Haibin Ling, Liangcai Gao, Qijie Zhao, Ling Cai, Tao Sheng, Ying Chen, Tingting Liang, Siwei Wang and Xiaohan Yi and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition and Applied Soft Computing.

In The Last Decade

Zhi Tang

120 papers receiving 2.0k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network

2019 637 citations Qijie Zhao, Yongtao Wang et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhi Tang China	21	1.6k	604	267	196	163	131	2.1k
Zhenmin Tang China	27	1.3k 0.8×	872 1.4×	210 0.8×	400 2.0×	124 0.8×	221	2.6k
Heming Jia China	22	604 0.4×	952 1.6×	216 0.8×	331 1.7×	96 0.6×	57	1.7k
Mukesh Saraswat India	21	746 0.5×	948 1.6×	238 0.9×	134 0.7×	43 0.3×	66	1.8k
Yiannis S. Boutalis Greece	25	837 0.5×	855 1.4×	178 0.7×	113 0.6×	94 0.6×	131	2.4k
Abdellatif Mtibaa Tunisia	21	838 0.5×	398 0.7×	126 0.5×	213 1.1×	38 0.2×	179	1.7k
Liujuan Cao China	24	1.9k 1.2×	940 1.6×	230 0.9×	66 0.3×	131 0.8×	108	2.7k
Fazhi He China	23	856 0.5×	519 0.9×	233 0.9×	97 0.5×	98 0.6×	68	1.7k
Hao Gao China	18	613 0.4×	503 0.8×	153 0.6×	151 0.8×	108 0.7×	116	1.4k
P. Nagabhushan India	22	973 0.6×	413 0.7×	348 1.3×	54 0.3×	58 0.4×	135	1.5k
Xu-Yao Zhang China	27	2.4k 1.5×	1.5k 2.5×	802 3.0×	48 0.2×	78 0.5×	115	3.4k

Countries citing papers authored by Zhi Tang

Since Specialization

Citations

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

Fields of papers citing papers by Zhi Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhi Tang

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Tang, Zhi. (2025). Application of ARIMA model in classification and prediction of athlete training data. Journal of Computational Methods in Sciences and Engineering. 25(1). 850–862.

Gao, Liangcai, et al.. (2022). A survey on table recognition technology. Journal of Image and Graphics. 27(6). 1898–1917. 2 indexed citations

Liang, Tingting, Yongtao Wang, Zhi Tang, Guosheng Hu, & Haibin Ling. (2021). OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection. 10190–10198. 46 indexed citations

Zhang, Xiaode, et al.. (2021). ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition. 4566–4572. 9 indexed citations

Wang, Siwei, Yongtao Wang, Xiaoran Qin, Qijie Zhao, & Zhi Tang. (2019). Scene Text Recognition via Gated Cascade Attention. 1018–1023. 5 indexed citations

Gao, Liangcai, et al.. (2017). A Deep Learning-Based Formula Detection Method for PDF Documents. 553–558. 20 indexed citations

Wang, Yongtao, et al.. (2017). SReN: Shape Regression Network for Comic Storyboard Extraction. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 6 indexed citations

Liao, Yuan, et al.. (2017). Deep-learning-based object-level contour detection with CCG and CRF optimization. 859–864. 10 indexed citations

Gao, Liangcai, Ke Yuan, Yuehan Wang, Zhuoren Jiang, & Zhi Tang. (2016). The Math Retrieval System of ICST for NTCIR-12 MathIR Task.. NTCIR. 7 indexed citations

10.

Wang, Yongtao, et al.. (2015). A tree conditional random field model for panel detection in comic images. Pattern Recognition. 48(7). 2129–2140. 9 indexed citations

11.

Wang, Yongtao, et al.. (2015). Comic frame extraction via line segments combination. 856–860. 13 indexed citations

12.

Wang, Yongtao, et al.. (2014). Comic2CEBX: a system for automatic comic content adaptation. 299–308. 1 indexed citations

13.

Gao, Liangcai, et al.. (2014). ICST Math Retrieval System for NTCIR-11 Math-2 Task. NTCIR. 6 indexed citations

14.

Liu, Dong, Yongtao Wang, Zhi Tang, & Xiaoqing Lu. (2014). A robust and fast line segment detector based on top-down smaller eigenvalue analysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9069. 906916–906916. 3 indexed citations

15.

Liu, Yan, et al.. (2013). Review of chart recognition in document images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8654. 865410–865410. 20 indexed citations

16.

Wang, Yongtao, et al.. (2013). Comic image understanding based on polygon detection. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8658. 86580B–86580B. 9 indexed citations

17.

Tang, Zhi, et al.. (2011). A decentralized authorization scheme for DRM in P2P file-sharing systems. 5473. 136–140. 7 indexed citations

18.

Tang, Zhi, et al.. (2009). Effects of the preoperative administration of Yunnan Baiyao capsules on intraoperative blood loss in bimaxillary orthognathic surgery: A prospective, randomized, double-blind, placebo-controlled study. International Journal of Oral and Maxillofacial Surgery. 38(3). 261–266. 32 indexed citations

19.

Gao, Liangcai, Zhi Tang, Xiaofan Lin, Xin Tao, & Yimin Chu. (2009). Analysis of book documents' table of content based on clustering. 911–915. 10 indexed citations

20.

Tang, Zhi. (2007). Progress of research on digital watermarking techniques applied to multimedia. Computer Engineering and Applications Journal.

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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