Shuai Lu

1.6k total citations
41 papers, 457 citations indexed

About

Shuai Lu is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Industrial and Manufacturing Engineering. According to data from OpenAlex, Shuai Lu has authored 41 papers receiving a total of 457 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 14 papers in Media Technology and 14 papers in Industrial and Manufacturing Engineering. Recurrent topics in Shuai Lu's work include Industrial Vision Systems and Defect Detection (14 papers), Image Processing Techniques and Applications (11 papers) and Retinal Imaging and Analysis (9 papers). Shuai Lu is often cited by papers focused on Industrial Vision Systems and Defect Detection (14 papers), Image Processing Techniques and Applications (11 papers) and Retinal Imaging and Analysis (9 papers). Shuai Lu collaborates with scholars based in China, United States and Hong Kong. Shuai Lu's co-authors include Le Yao, Huiqi Li, Sergei V. Pereverzev, Xiang Xu, Ningli Wang, Hanruo Liu, Yongli Xu, Qun Li, Hao Han and Weihang Zhang and has published in prestigious journals such as Journal of Materials Chemistry A, IEEE Transactions on Image Processing and Expert Systems with Applications.

In The Last Decade

Shuai Lu

36 papers receiving 432 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuai Lu China	13	134	118	90	87	82	41	457
Chunwei Song China	10	271 2.0×	24 0.2×	76 0.8×	16 0.2×	84 1.0×	25	472
Joaquin Zepeda France	5	203 1.5×	195 1.7×	488 5.4×	77 0.9×	134 1.6×	9	676
Latha Pemula Germany	1	155 1.2×	194 1.6×	469 5.2×	72 0.8×	134 1.6×	2	622
Zhengmao Ye United States	10	163 1.2×	19 0.2×	41 0.5×	25 0.3×	53 0.6×	88	447
Sylvain Durand France	13	263 2.0×	9 0.1×	31 0.3×	16 0.2×	127 1.5×	68	678
Sendren Sheng‐Dong Xu Taiwan	13	109 0.8×	26 0.2×	61 0.7×	24 0.3×	84 1.0×	46	651
R. Jagadeesh Kannan India	12	122 0.9×	6 0.1×	92 1.0×	30 0.3×	366 4.5×	88	610
Hong Cai United States	13	329 2.5×	37 0.3×	65 0.7×	15 0.2×	97 1.2×	54	634
Qiyue Xie China	12	100 0.7×	18 0.2×	101 1.1×	5 0.1×	415 5.1×	50	819
Yue Zhao China	10	225 1.7×	156 1.3×	85 0.9×	7 0.1×	18 0.2×	72	544

Countries citing papers authored by Shuai Lu

Since Specialization

Citations

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

Fields of papers citing papers by Shuai Lu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuai Lu

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

Lu, Shuai, et al.. (2025). A diverse embedding-based composite reconstruction encoder–decoder for color fabric defect detection. Expert Systems with Applications. 278. 127261–127261.

Lu, Shuai, et al.. (2025). Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection. 20405–20415. 6 indexed citations

Luo, Yu, et al.. (2025). Multi‐LiDAR‐Based 3D Object Detection via Data‐Level Fusion Method. International Journal of Antennas and Propagation. 2025(1).

Xia, Jiuyang, Jianghong Zhang, Kang Huang, et al.. (2024). In situ growth of an active catalytic layer on commercial stainless steel via a hydrothermal-assisted corrosion process for efficient oxygen evolution reaction. Journal of Materials Chemistry A. 12(30). 19008–19017. 3 indexed citations

Lu, Shuai, et al.. (2024). PatchCL-AE: Anomaly detection for medical images using patch-wise contrastive learning-based auto-encoder. Computerized Medical Imaging and Graphics. 114. 102366–102366. 9 indexed citations

Lu, Shuai, et al.. (2024). Masked contrastive generative adversarial network for defect detection of yarn-dyed fabric. The Journal of Supercomputing. 81(1). 1 indexed citations

Lu, Shuai, He Zhao, Hanruo Liu, Huiqi Li, & Ningli Wang. (2023). PKRT-Net: Prior knowledge-based relation transformer network for optic cup and disc segmentation. Neurocomputing. 538. 126183–126183. 21 indexed citations

Lu, Shuai, et al.. (2023). Knowledge distillation for unsupervised defect detection of yarn‐dyed fabric using the system DAERD: Dual attention embedded reconstruction distillation. Coloration Technology. 140(1). 125–143. 9 indexed citations

Wu, Yanzi, et al.. (2023). A mixed‐attention‐based multi‐scale autoencoder algorithm for fabric defect detection. Coloration Technology. 140(3). 451–466. 1 indexed citations

10.

Lu, Shuai, et al.. (2023). QA-USTNet: Yarn-dyed fabric defect detection via U-shaped Swin Transformer Network based on Quadtree Attention. Textile Research Journal. 93(15-16). 3492–3508. 16 indexed citations

11.

Wang, Chi, et al.. (2023). Color-patterned fabric defect detection algorithm based on triplet attention multi-scale U-shape denoising convolutional auto-encoder. The Journal of Supercomputing. 80(4). 4451–4476. 10 indexed citations

12.

Tian, Hang, Shuai Lu, Yun Sun, & Huiqi Li. (2022). GC-Net: Global and Class Attention Blocks for Automated Glaucoma Classification. 498–503. 5 indexed citations

13.

Zhang, Weiwei, et al.. (2022). Colour‐patterned fabric‐defect detection using unsupervised and memorial defect‐free features. Coloration Technology. 138(6). 602–620. 7 indexed citations

14.

Xu, Yongli, Man Hu, Hanruo Liu, et al.. (2021). A hierarchical deep learning approach with transparency and interpretability based on small samples for glaucoma diagnosis. npj Digital Medicine. 4(1). 48–48. 33 indexed citations

15.

Zhou, Rui, Xiang Lu, Shuai Lu, Yang Fu, & Mingjie Tang. (2020). Phone Position Independent Recognition of FineWalking Modes with Phone Sensors.. 46. 139–161. 1 indexed citations

16.

Ye, Liang, et al.. (2020). Unsupervised noise-robust feature extraction for aerial image classification. Science China Technological Sciences. 63(8). 1406–1415. 8 indexed citations

17.

Sun, Jianbin, et al.. (2019). A new modeling and inference approach for the belief rule base with attribute reliability. Applied Intelligence. 50(3). 976–992. 11 indexed citations

18.

Xu, Yongli, Shuai Lu, Han‐Xiong Li, & Ruirui Li. (2019). Mixed Maximum Loss Design for Optic Disc and Optic Cup Segmentation with Deep Learning from Imbalanced Samples. Sensors. 19(20). 4401–4401. 22 indexed citations

19.

Zhao, Zhuofeng, Shuai Lu, & Yanbo Han. (2017). Similar trajectory query method based on massive vehicle license plate recognition data. Journal of Tsinghua University(Science and Technology). 57(2). 220–224. 1 indexed citations

20.

Cao, Jiannong, et al.. (2009). Sleeping Schedule-Aware Minimum Latency Broadcast in Wireless Ad Hoc Networks. PolyU Institutional Research Archive (Hong Kong Polytechnic University). 1–5. 27 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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