Linhao Shao

565 total citations · 1 hit paper
8 papers, 359 citations indexed

About

Linhao Shao is a scholar working on Industrial and Manufacturing Engineering, Civil and Structural Engineering and Computational Mechanics. According to data from OpenAlex, Linhao Shao has authored 8 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Industrial and Manufacturing Engineering, 4 papers in Civil and Structural Engineering and 4 papers in Computational Mechanics. Recurrent topics in Linhao Shao's work include Industrial Vision Systems and Defect Detection (5 papers), Infrastructure Maintenance and Monitoring (4 papers) and Surface Roughness and Optical Measurements (4 papers). Linhao Shao is often cited by papers focused on Industrial Vision Systems and Defect Detection (5 papers), Infrastructure Maintenance and Monitoring (4 papers) and Surface Roughness and Optical Measurements (4 papers). Linhao Shao collaborates with scholars based in China. Linhao Shao's co-authors include Erhu Zhang, Yajun Chen, Yuanyuan Ding, Fan Zhao, Q. Ma, Yang Wang, Erhu Zhang and Qing Zhang and has published in prestigious journals such as Automation in Construction, IEEE Transactions on Instrumentation and Measurement and Applied Sciences.

In The Last Decade

Linhao Shao

8 papers receiving 345 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.

Surface Defect Detection Methods for Industrial Products: A Review

2021 225 citations Yajun Chen, Yuanyuan Ding et al. Applied Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Linhao Shao China	7	264	142	110	88	59	8	359
Chunhua Yang China	4	304 1.2×	163 1.1×	97 0.9×	118 1.3×	102 1.7×	6	403
Zhonghe Ren China	4	249 0.9×	134 0.9×	44 0.4×	97 1.1×	55 0.9×	6	398
Jianwei Liu China	9	134 0.5×	88 0.6×	159 1.4×	126 1.4×	51 0.9×	21	321
Xingjie Li China	4	187 0.7×	125 0.9×	41 0.4×	108 1.2×	53 0.9×	13	287
Ying Tian China	8	334 1.3×	175 1.2×	81 0.7×	137 1.6×	111 1.9×	29	399
Swarit Anand Singh India	5	164 0.6×	73 0.5×	38 0.3×	100 1.1×	57 1.0×	15	238
Doo-chul Choi South Korea	13	305 1.2×	145 1.0×	82 0.7×	100 1.1×	152 2.6×	19	374
Zhenxia Ke China	6	136 0.5×	125 0.9×	25 0.2×	38 0.4×	37 0.6×	8	266
Junfeng Jing China	11	227 0.9×	151 1.1×	66 0.6×	30 0.3×	68 1.2×	34	361

Countries citing papers authored by Linhao Shao

Since Specialization

Citations

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

Fields of papers citing papers by Linhao Shao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linhao Shao

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

All Works

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8 of 8 papers shown

1.

Shao, Linhao, et al.. (2023). Enriched multi-scale cascade pyramid features and guided context attention network for industrial surface defect detection. Engineering Applications of Artificial Intelligence. 123. 106369–106369. 21 indexed citations

2.

Ma, Q., et al.. (2023). SIA-net: Structural information awareness network based on normal samples for surface defect detection. Engineering Applications of Artificial Intelligence. 126. 107131–107131. 7 indexed citations

3.

Zhang, Erhu, et al.. (2022). An inverse halftoning method for various types of halftone images based on multi-scale generative adversarial network. Engineering Applications of Artificial Intelligence. 117. 105600–105600. 1 indexed citations

4.

Zhang, Erhu, et al.. (2022). EGD-Net: Edge-guided and differential attention network for surface defect detection. Journal of Industrial Information Integration. 30. 100403–100403. 16 indexed citations

5.

Zhang, Erhu, Linhao Shao, & Yang Wang. (2022). Unifying transformer and convolution for dam crack detection. Automation in Construction. 147. 104712–104712. 51 indexed citations

6.

Shao, Linhao, et al.. (2022). Pixel-Wise Semisupervised Fabric Defect Detection Method Combined With Multitask Mean Teacher. IEEE Transactions on Instrumentation and Measurement. 71. 1–11. 31 indexed citations

7.

Chen, Yajun, et al.. (2021). Surface Defect Detection Methods for Industrial Products: A Review. Applied Sciences. 11(16). 7657–7657. 225 indexed citations breakdown →

8.

Shao, Linhao, et al.. (2021). An Efficient Convolutional Neural Network Model Combined with Attention Mechanism for Inverse Halftoning. Electronics. 10(13). 1574–1574. 7 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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