Peibei Shi

408 total citations
16 papers, 235 citations indexed

About

Peibei Shi is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality and Statistics and Probability. According to data from OpenAlex, Peibei Shi has authored 16 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 4 papers in Safety, Risk, Reliability and Quality and 3 papers in Statistics and Probability. Recurrent topics in Peibei Shi's work include Video Surveillance and Tracking Methods (5 papers), Fire Detection and Safety Systems (4 papers) and Statistical Methods and Inference (2 papers). Peibei Shi is often cited by papers focused on Video Surveillance and Tracking Methods (5 papers), Fire Detection and Safety Systems (4 papers) and Statistical Methods and Inference (2 papers). Peibei Shi collaborates with scholars based in China and United States. Peibei Shi's co-authors include Zhong Wang, Narasimhan Danthi, Colin O. Wu, Michael S. Lauer, Tong Li, Lei Wu, Ke Ma, Chao Wu, Annie Qu and Lan Xue and has published in prestigious journals such as Circulation Research, Statistics in Medicine and The Annals of Statistics.

In The Last Decade

Peibei Shi

15 papers receiving 225 citations

Peers

Peibei Shi

CVPR

SPU

SRRQ

PHEOH

EE

Zhongjie Lin United States

Fan Zuo United States

José Mira Spain

Han-Guk Ryu South Korea

Mao Tian China

Anh Nguyen Vietnam

Jianliang Zhou China

Rui Carvalho United Kingdom

Minhyuk Jung South Korea

Da Lei China

Zhongjie Lin United States

Peibei Shi

52 ×0.7

CVPR

4 ×0.1

SPU

34 ×1.0

SRRQ

8 ×0.2

PHEOH

11 ×0.4

EE

Citations per year, relative to Peibei Shi Peibei Shi (= 1×) peers Zhongjie Lin

Countries citing papers authored by Peibei Shi

Since Specialization

Citations

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

Fields of papers citing papers by Peibei Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peibei Shi

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

All Works

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16 of 16 papers shown

1.

Wang, Zhong, et al.. (2025). RT-DETR-Smoke: A Real-Time Transformer for Forest Smoke Detection. Fire. 8(5). 170–170. 1 indexed citations

2.

Wang, Zhong, et al.. (2024). Smoking-YOLOv8: a novel smoking detection algorithm for chemical plant personnel. Pattern Analysis and Applications. 27(3). 3 indexed citations

3.

Ma, Ke, et al.. (2023). YOLOv7-CSAW for maritime target detection. Frontiers in Neurorobotics. 17. 1210470–1210470. 31 indexed citations

4.

Wang, Zhong, et al.. (2023). Smoking behavior detection algorithm based on YOLOv8-MNC. Frontiers in Computational Neuroscience. 17. 1243779–1243779. 17 indexed citations

5.

Wang, Zhong, Lei Wu, Tong Li, & Peibei Shi. (2022). A Smoke Detection Model Based on Improved YOLOv5. Mathematics. 10(7). 1190–1190. 51 indexed citations

6.

Wang, Zhong, et al.. (2022). Face Mask-Wearing Detection Model Based on Loss Function and Attention Mechanism. Computational Intelligence and Neuroscience. 2022. 1–10. 9 indexed citations

7.

Wang, Zhong & Peibei Shi. (2021). CAPTCHA Recognition Method Based on CNN with Focal Loss. Complexity. 2021(1). 10 indexed citations

8.

Shi, Peibei & Zhong Wang. (2021). An Ensemble Tree Classifier for Highly Imbalanced Data Classification. Journal of Systems Science and Complexity. 34(6). 2250–2266. 6 indexed citations

9.

Wang, Zhong & Peibei Shi. (2021). Research and Analysis on the Index System of Digital Economy in Anhui Province. Complexity. 2021(1). 30 indexed citations

10.

Wang, Zhong, Peibei Shi, & Chao Wu. (2020). A Fatigue Driving Detection Method based on Deep Learning and Image Processing. Journal of Physics Conference Series. 1575(1). 12035–12035. 4 indexed citations

11.

Wang, Zhong, Peibei Shi, & Chao Wu. (2020). A Ship Draft Line Detection Method Based on Image Processing and Deep Learning. Journal of Physics Conference Series. 1575(1). 12230–12230. 7 indexed citations

12.

Shi, Peibei, et al.. (2019). Reliability Modeling and Analysis of Ship Communication Network Based on Apriori Algorithm. Journal of Coastal Research. 93(sp1). 711–711. 2 indexed citations

13.

Xue, Lan, et al.. (2019). Time‐varying feature selection for longitudinal analysis. Statistics in Medicine. 39(2). 156–170.

14.

Shi, Peibei & Annie Qu. (2017). Weak signal identification and inference in penalized model selection. The Annals of Statistics. 45(3). 4 indexed citations

15.

Danthi, Narasimhan, Colin O. Wu, Peibei Shi, & Michael S. Lauer. (2014). Percentile Ranking and Citation Impact of a Large Cohort of National Heart, Lung, and Blood Institute–Funded Cardiovascular R01 Grants. Circulation Research. 114(4). 600–606. 58 indexed citations

16.

Shi, Peibei. (2009). Pedestrian Detection Method Based on Improved AdaBoost Algorithm. 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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