Kechen Song

7.1k total citations · 4 hit papers
144 papers, 5.1k citations indexed

About

Kechen Song is a scholar working on Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering and Mechanical Engineering. According to data from OpenAlex, Kechen Song has authored 144 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Computer Vision and Pattern Recognition, 50 papers in Industrial and Manufacturing Engineering and 34 papers in Mechanical Engineering. Recurrent topics in Kechen Song's work include Industrial Vision Systems and Defect Detection (50 papers), Advanced Neural Network Applications (31 papers) and Infrastructure Maintenance and Monitoring (28 papers). Kechen Song is often cited by papers focused on Industrial Vision Systems and Defect Detection (50 papers), Advanced Neural Network Applications (31 papers) and Infrastructure Maintenance and Monitoring (28 papers). Kechen Song collaborates with scholars based in China, United Kingdom and Japan. Kechen Song's co-authors include Yunhui Yan, Yu He, Qinggang Meng, Hongwen Dong, Liming Huang, Jing Xu, Menghui Niu, Yanyan Wang, Yanqi Bao and Jie Wang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Industrial Electronics.

In The Last Decade

Kechen Song

128 papers receiving 5.0k citations

Hit Papers

An End-to-End Steel Surface Defect Detection A... 2013 2026 2017 2021 2019 2013 2019 2021 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kechen Song China 35 3.1k 2.6k 1.3k 1.2k 1.0k 144 5.1k
Yunhui Yan China 35 3.1k 1.0× 2.7k 1.0× 1.3k 1.0× 1.2k 1.0× 1.1k 1.0× 164 5.3k
De Xu China 32 1.1k 0.4× 2.2k 0.8× 986 0.7× 273 0.2× 251 0.2× 269 4.3k
Jing Xu China 32 471 0.2× 1.6k 0.6× 2.0k 1.5× 123 0.1× 285 0.3× 173 4.4k
Jorge Angeles Canada 49 1.6k 0.5× 1.2k 0.5× 3.2k 2.4× 517 0.4× 662 0.6× 423 11.7k
Junfeng Fan China 27 542 0.2× 771 0.3× 851 0.6× 155 0.1× 126 0.1× 111 2.2k
Dikai Liu Australia 28 483 0.2× 617 0.2× 599 0.5× 478 0.4× 67 0.1× 228 2.9k
Du Jiang China 40 596 0.2× 1.5k 0.6× 376 0.3× 133 0.1× 106 0.1× 98 3.6k
Song Yao China 31 229 0.1× 1.4k 0.5× 1.0k 0.8× 594 0.5× 187 0.2× 102 4.1k
Sang Woo Kim South Korea 29 494 0.2× 458 0.2× 441 0.3× 165 0.1× 414 0.4× 191 2.7k
Jianyi Kong China 29 465 0.1× 990 0.4× 373 0.3× 153 0.1× 113 0.1× 112 2.9k

Countries citing papers authored by Kechen Song

Since Specialization
Citations

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

Fields of papers citing papers by Kechen Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kechen Song

This figure shows the co-authorship network connecting the top 25 collaborators of Kechen Song. A scholar is included among the top collaborators of Kechen Song 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 Kechen Song. Kechen Song 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.
Wang, Yanyan, Kechen Song, Yuyuan Liu, et al.. (2025). Leveraging labelled data knowledge: A cooperative rectification learning network for semi-supervised 3D medical image segmentation. Medical Image Analysis. 101. 103461–103461. 5 indexed citations
2.
Li, Qingqing, et al.. (2024). An efficient tool for real-time global carbon neutrality with credibility of delicacy management: A Modelx + MRV + O system. Applied Energy. 372. 123763–123763. 1 indexed citations
3.
Song, Kechen, et al.. (2024). Nondestructive in-ovo sexing of Hy-Line Sonia eggs by EggFormer using hyperspectral imaging. Computers and Electronics in Agriculture. 225. 109298–109298. 6 indexed citations
4.
Song, Kechen, et al.. (2024). An efficient targeted design for real-time defect detection of surface defects. Optics and Lasers in Engineering. 178. 108174–108174. 8 indexed citations
5.
Yan, Yunhui, et al.. (2024). Uncertainty inspired domain adaptation network for rail surface defect segmentation. Engineering Applications of Artificial Intelligence. 135. 108860–108860. 5 indexed citations
6.
Song, Kechen, et al.. (2024). Will Government Digital Focus Affect Local Economic Development. Academic Journal of Science and Technology. 10(1). 442–444.
7.
Wang, Hai‐Kun, et al.. (2024). Sparse Transformer-based bins and Polarized Cross Attention decoder for monocular depth estimation. Engineering Science and Technology an International Journal. 54. 101705–101705. 1 indexed citations
8.
Xu, Jianwei, et al.. (2024). Analysis of abnormal bright band characteristics of forging for a new low-cost titanium alloy. Materials Letters. 369. 136746–136746. 2 indexed citations
9.
Song, Kechen, et al.. (2023). NFCF: Industrial Surface Anomaly Detection with Normalizing Flow Cross-Fitting Network. Optics and Lasers in Engineering. 168. 107655–107655. 6 indexed citations
10.
Ma, Shuai, Kechen Song, Menghui Niu, et al.. (2023). Feature-based domain disentanglement and randomization: A generalized framework for rail surface defect segmentation in unseen scenarios. Advanced Engineering Informatics. 59. 102274–102274. 18 indexed citations
11.
Song, Kechen, et al.. (2023). Exploring the potential of Siamese network for RGBT object tracking. Journal of Visual Communication and Image Representation. 95. 103882–103882. 10 indexed citations
12.
Song, Kechen, et al.. (2023). MFS enhanced SAM: Achieving superior performance in bimodal few-shot segmentation. Journal of Visual Communication and Image Representation. 97. 103946–103946. 7 indexed citations
13.
Song, Kechen, et al.. (2023). DASR: Dual-Attention Transformer for infrared image super-resolution. Infrared Physics & Technology. 133. 104837–104837. 15 indexed citations
14.
Song, Kechen, et al.. (2023). Balanced multi-scale target score network for ceramic tile surface defect detection. Measurement. 224. 113914–113914. 18 indexed citations
15.
Song, Kechen, et al.. (2023). Hierarchical Two-stage modal fusion for Triple-modality salient object detection. Measurement. 218. 113180–113180. 3 indexed citations
16.
Zhao, Wenli, et al.. (2023). FaNet: Feature-aware network for few shot classification of strip steel surface defects. Measurement. 208. 112446–112446. 38 indexed citations
17.
Tian, Hongkun, Kechen Song, Jing Xu, Shuai Ma, & Yunhui Yan. (2023). Antipodal-points-aware dual-decoding network for robotic visual grasp detection oriented to multi-object clutter scenes. Expert Systems with Applications. 230. 120545–120545. 10 indexed citations
18.
Song, Kechen, et al.. (2023). Modality Registration and Object Search Framework for UAV-Based Unregistered RGB-T Image Salient Object Detection. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–15. 12 indexed citations
19.
Song, Kechen, et al.. (2023). Cross-modality salient object detection network with universality and anti-interference. Knowledge-Based Systems. 264. 110322–110322. 25 indexed citations
20.
Song, Kechen, et al.. (2022). A Multi-Exposure Fusion Method for Reflection Suppression of Curved Workpieces. IEEE Transactions on Instrumentation and Measurement. 71. 1–4. 5 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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