Jinting Shi

707 total citations
21 papers, 574 citations indexed

About

Jinting Shi is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality and Business and International Management. According to data from OpenAlex, Jinting Shi has authored 21 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 16 papers in Safety, Risk, Reliability and Quality and 1 paper in Business and International Management. Recurrent topics in Jinting Shi's work include Fire Detection and Safety Systems (16 papers), Video Surveillance and Tracking Methods (15 papers) and Image Enhancement Techniques (13 papers). Jinting Shi is often cited by papers focused on Fire Detection and Safety Systems (16 papers), Video Surveillance and Tracking Methods (15 papers) and Image Enhancement Techniques (13 papers). Jinting Shi collaborates with scholars based in China. Jinting Shi's co-authors include Feiniu Yuan, Xue Xia, Boyang Wan, Zhijian Yin, Yuming Fang, Lin Zhang, Zhijun Fang, Tao Mei, Gang Li and Hongdi Li and has published in prestigious journals such as IEEE Access, Pattern Recognition and Information Sciences.

In The Last Decade

Jinting Shi

20 papers receiving 555 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jinting Shi China 12 469 429 60 54 41 21 574
Detian Huang China 7 212 0.5× 123 0.3× 29 0.5× 40 0.7× 71 1.7× 30 318
Boyang Wan China 7 383 0.8× 324 0.8× 55 0.9× 35 0.6× 12 0.3× 10 546
Yinda Xu China 4 596 1.3× 148 0.3× 72 1.2× 58 1.1× 32 0.8× 6 672
Kasım Taşdemir Türkiye 10 187 0.4× 108 0.3× 37 0.6× 27 0.5× 14 0.3× 28 322
Zehua Fu China 5 441 0.9× 69 0.2× 38 0.6× 25 0.5× 31 0.8× 12 513
Gaohua Lin China 8 411 0.9× 486 1.1× 136 2.3× 75 1.4× 13 0.3× 8 517
Yang Feng China 8 207 0.4× 86 0.2× 50 0.8× 16 0.3× 105 2.6× 35 341
Michael Del Rose Italy 8 327 0.7× 67 0.2× 23 0.4× 34 0.6× 31 0.8× 12 369
Kenan Dai China 5 514 1.1× 148 0.3× 72 1.2× 57 1.1× 15 0.4× 5 540

Countries citing papers authored by Jinting Shi

Since Specialization
Citations

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

Fields of papers citing papers by Jinting Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jinting Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Jinting Shi. A scholar is included among the top collaborators of Jinting 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 Jinting Shi. Jinting Shi 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
1.
2.
Yuan, Feiniu, et al.. (2023). A multiple gated boosting network for multi‐organ medical image segmentation. IET Image Processing. 17(10). 3028–3039. 4 indexed citations
3.
Yuan, Feiniu, et al.. (2022). Cubic-cross convolutional attention and count prior embedding for smoke segmentation. Pattern Recognition. 131. 108902–108902. 24 indexed citations
4.
Yuan, Feiniu, et al.. (2022). Fully extracting feature correlation between and within stages for semantic segmentation. Digital Signal Processing. 127. 103578–103578. 11 indexed citations
5.
Shi, Jinting. (2022). E-Commerce Products Personalized Recommendation Based on Deep Learning. 1–5. 3 indexed citations
6.
Yuan, Feiniu, et al.. (2022). An anisotropic non-local attention network for image segmentation. Machine Vision and Applications. 33(2). 3 indexed citations
7.
Yuan, Feiniu, Yu Zhou, Xue Xia, et al.. (2020). Image dehazing based on a transmission fusion strategy by automatic image matting. Computer Vision and Image Understanding. 194. 102933–102933. 16 indexed citations
8.
Yuan, Feiniu, Gang Li, Xue Xia, Jinting Shi, & Lin Zhang. (2020). Encoding features from multi-layer Gabor filtering for visual smoke recognition. Pattern Analysis and Applications. 23(3). 1117–1131. 5 indexed citations
9.
Xia, Xue, et al.. (2019). From traditional methods to deep ones: review of visual smoke recognition, detection, and segmentation. Journal of Image and Graphics. 24(10). 1627–1647. 11 indexed citations
10.
Yuan, Feiniu, et al.. (2019). Dual-Encoded Features from Both Spatial and Curvelet Domains for Image Smoke Recognition. KSII Transactions on Internet and Information Systems. 13(4). 1 indexed citations
11.
Yuan, Feiniu, Gang Li, Xue Xia, Bangjun Lei, & Jinting Shi. (2019). Fusing texture, edge and line features for smoke recognition. IET Image Processing. 13(14). 2805–2812. 12 indexed citations
12.
Yuan, Feiniu, Xue Xia, & Jinting Shi. (2018). Holistic learning-based high-order feature descriptor for smoke recognition. International Journal of Wavelets Multiresolution and Information Processing. 17(2). 1940005–1940005. 6 indexed citations
13.
Yuan, Feiniu, Jinting Shi, Xue Xia, Qinghua Huang, & Xuelong Li. (2018). Co‐occurrence matching of local binary patterns for improving visual adaption and its application to smoke recognition. IET Computer Vision. 13(2). 178–187. 10 indexed citations
14.
Yuan, Feiniu, Xue Xia, & Jinting Shi. (2018). Mixed co-occurrence of local binary patterns and Hamming-distance-based local binary patterns. Information Sciences. 460-461. 202–222. 21 indexed citations
15.
Yuan, Feiniu, Jinting Shi, Xue Xia, Lin Zhang, & Shuying Li. (2018). Encoding pairwise Hamming distances of Local Binary Patterns for visual smoke recognition. Computer Vision and Image Understanding. 178. 43–53. 18 indexed citations
16.
Yuan, Feiniu, Xue Xia, Jinting Shi, Lin Zhang, & Jifeng Huang. (2018). Learning multi-scale and multi-order features from 3D local differences for visual smoke recognition. Information Sciences. 468. 193–212. 12 indexed citations
17.
Yin, Zhijian, Boyang Wan, Feiniu Yuan, Xue Xia, & Jinting Shi. (2017). A Deep Normalization and Convolutional Neural Network for Image Smoke Detection. IEEE Access. 5. 18429–18438. 210 indexed citations
18.
Yuan, Feiniu, Xue Xia, Jinting Shi, Hongdi Li, & Gang Li. (2017). Non-Linear Dimensionality Reduction and Gaussian Process Based Classification Method for Smoke Detection. IEEE Access. 5. 6833–6841. 36 indexed citations
19.
Yuan, Feiniu, Jinting Shi, Xue Xia, et al.. (2016). Sub Oriented Histograms of Local Binary Patterns for Smoke Detection and Texture Classification. KSII Transactions on Internet and Information Systems. 10(4). 27 indexed citations
20.
Yuan, Feiniu, Jinting Shi, Xue Xia, et al.. (2016). High-order local ternary patterns with locality preserving projection for smoke detection and image classification. Information Sciences. 372. 225–240. 88 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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