Shuai Shao

3.1k total citations · 2 hit papers
27 papers, 1.2k citations indexed

About

Shuai Shao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology. According to data from OpenAlex, Shuai Shao has authored 27 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 8 papers in Artificial Intelligence and 4 papers in Media Technology. Recurrent topics in Shuai Shao's work include Advanced Image and Video Retrieval Techniques (5 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Neural Network Applications (4 papers). Shuai Shao is often cited by papers focused on Advanced Image and Video Retrieval Techniques (5 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Neural Network Applications (4 papers). Shuai Shao collaborates with scholars based in China, India and United States. Shuai Shao's co-authors include Gang Yu, Enze Xie, Xiang Li, Wenhai Wang, Tong Lü, Xiangyu Zhang, Chao Peng, Jian Sun, Jing Li and Zeming Li and has published in prestigious journals such as IEEE Transactions on Image Processing, IEEE Access and Neurocomputing.

In The Last Decade

Shuai Shao

22 papers receiving 1.1k citations

Hit Papers

align trajectories

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.

Shape Robust Text Detection With Progressive Scale Expansion Network

2019 451 citations Enze Xie, Gang Yu et al. profile →
Objects365: A Large-Scale, High-Quality Dataset for Object Detection

2019 373 citations Shuai Shao, Zeming Li et al. profile →

Peers

Shuai Shao

CVPR

MT

AI

OE

SRRQ

Mingliang Gao China

Shilong Liu China

Jun Hao Liew Singapore

Ping Han China

Shaohua Qiu China

Yongqiang Yao China

Dayan Guan Singapore

Yingtian Zou Singapore

Yiquan Wu China

Mingliang Gao China

Shuai Shao

685 ×0.8

CVPR

289 ×0.7

MT

302 ×1.0

AI

55 ×0.9

OE

58 ×1.1

SRRQ

Citations per year, relative to Shuai Shao Shuai Shao (= 1×) peers Mingliang Gao

Countries citing papers authored by Shuai Shao

Since Specialization

Citations

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

Fields of papers citing papers by Shuai Shao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuai Shao

This figure shows the co-authorship network connecting the top 25 collaborators of Shuai Shao. A scholar is included among the top collaborators of Shuai Shao 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 Shuai Shao. Shuai Shao 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

1.

Shao, Shuai, et al.. (2025). Advanced fault diagnostics in rotating machinery: A deep learning approach using octave theory of dynamic vibration signals. Journal of Vibration and Control. 32(7-8). 1514–1527.

2.

Wu, Yushan, Jitao Zhong, Lu Zhang, et al.. (2024). Locality-constrained robust discriminant non-negative matrix factorization for depression detection: An fNIRS study. Neurocomputing. 617. 128887–128887.

3.

Chen, Junyi, et al.. (2024). EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE. Proceedings of the AAAI Conference on Artificial Intelligence. 38(2). 1110–1119. 1 indexed citations

4.

Shao, Shuai, et al.. (2024). A general kinematic approach to the effect of rock mass saturation on the stability of 3D rock slopes. Environmental Earth Sciences. 84(1).

5.

Guo, Longteng, et al.. (2023). MAMO: Fine-Grained Vision-Language Representations Learning with Masked Multimodal Modeling. 1528–1538. 5 indexed citations

6.

Li, Cong, Shuying Wang, Xiang Gao, et al.. (2023). A unifying review of edge intelligent computing technique applications in the field of energy networks. Journal of Industrial and Management Optimization. 19(11). 7966–7992.

7.

Cheng, Juan, et al.. (2022). A Reverberation Noise Suppression Method of Sonar Image Based on Shearlet Transform. IEEE Sensors Journal. 23(3). 2672–2683. 12 indexed citations

8.

Lian, Zhichao, et al.. (2020). A Real Time Face Tracking System based on Multiple Information Fusion. Multimedia Tools and Applications. 79(23-24). 16751–16769. 12 indexed citations

9.

Wang, Bin, et al.. (2020). Automatic Modulation Classification for Short Burst Underwater Acoustic Communication Signals Based on Hybrid Neural Networks. IEEE Access. 8. 227793–227809. 18 indexed citations

10.

Shao, Shuai, Zeming Li, Tianyuan Zhang, et al.. (2019). Objects365: A Large-Scale, High-Quality Dataset for Object Detection. 8429–8438. 373 indexed citations breakdown →

11.

Shao, Shuai, et al.. (2019). A Study on Cosine Efficiency in a Tower Reflector Solar Power System. 4224–4227. 1 indexed citations

12.

Shao, Shuai, et al.. (2019). Semi-Supervised Structured Sparse Graph Data Classification. 100–103. 2 indexed citations

13.

Xie, Enze, Yuhang Zang, Shuai Shao, et al.. (2019). Scene Text Detection with Supervised Pyramid Context Network. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 9038–9045. 150 indexed citations

14.

Shao, Shuai, et al.. (2018). Scene text detection based on enhanced multi-channels MSER and a fast text grouping process. 351–355. 9 indexed citations

15.

Li, Haibo, et al.. (2017). Failure Mechanisms and Evolution Assessment of the Excavation Damaged Zones in a Large-Scale and Deeply Buried Underground Powerhouse. Rock Mechanics and Rock Engineering. 50(7). 1883–1900. 45 indexed citations

16.

Shao, Shuai, Xing-guo Yang, & Jia‐wen Zhou. (2016). Numerical analysis of different ventilation schemes during the construction process of inclined tunnel groups at the Changheba Hydropower Station, China. Tunnelling and Underground Space Technology. 59. 157–169. 35 indexed citations

17.

Li, Bo, Tianfu Wu, Shuai Shao, Lun Zhang, & Rufeng Chu. (2016). Object Detection via End-to-End Integration of Aspect Ratio and Context Aware Part-based Models and Fully Convolutional Networks.. 3 indexed citations

18.

Shao, Shuai, Fuqing Duan, & Ping Guo. (2012). Image Segmentation Based on Visual Perception Model. 1 indexed citations

19.

Duan, Haibin, et al.. (2009). Adaptive Template Matching Based on Improved Ant Colony Optimization. 1–4. 2 indexed citations

20.

Shao, Shuai & Mei Xie. (2006). Kernel-based Classifier for Iris Recognition. 1 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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