Minghao Piao

1.1k total citations
39 papers, 726 citations indexed

About

Minghao Piao is a scholar working on Electrical and Electronic Engineering, Industrial and Manufacturing Engineering and Artificial Intelligence. According to data from OpenAlex, Minghao Piao has authored 39 papers receiving a total of 726 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Electrical and Electronic Engineering, 11 papers in Industrial and Manufacturing Engineering and 9 papers in Artificial Intelligence. Recurrent topics in Minghao Piao's work include Industrial Vision Systems and Defect Detection (11 papers), Integrated Circuits and Semiconductor Failure Analysis (7 papers) and Advancements in Photolithography Techniques (4 papers). Minghao Piao is often cited by papers focused on Industrial Vision Systems and Defect Detection (11 papers), Integrated Circuits and Semiconductor Failure Analysis (7 papers) and Advancements in Photolithography Techniques (4 papers). Minghao Piao collaborates with scholars based in South Korea, China and Japan. Minghao Piao's co-authors include Keun Ho Ryu, Cheng Jin, Jong Yun Lee, Yongjun Piao, Gouchol Pok, Ho Sun Shon, Muhammad Saqlain, Kiejung Park, Meijing Li and Zhengbiao Zhang and has published in prestigious journals such as Bioinformatics, ACS Applied Materials & Interfaces and IEEE Transactions on Power Systems.

In The Last Decade

Minghao Piao

34 papers receiving 693 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Minghao Piao South Korea 12 323 300 122 110 108 39 726
Changyun Li China 16 102 0.3× 142 0.5× 130 1.1× 42 0.4× 88 0.8× 101 995
Danmin Chen China 12 65 0.2× 82 0.3× 155 1.3× 46 0.4× 120 1.1× 33 834
Qing-Hua Ling China 16 52 0.2× 141 0.5× 686 5.6× 244 2.2× 107 1.0× 51 1.1k
Maoqing Zhang China 15 39 0.1× 81 0.3× 204 1.7× 126 1.1× 28 0.3× 37 663
Ke Shang China 15 115 0.4× 141 0.5× 515 4.2× 156 1.4× 32 0.3× 89 1.1k
Mian Ahmad Jan Pakistan 8 46 0.1× 203 0.7× 90 0.7× 39 0.4× 123 1.1× 8 618
Sheng Liu China 13 167 0.5× 53 0.2× 299 2.5× 146 1.3× 32 0.3× 64 583
Cheng‐Hsiung Lee Taiwan 12 218 0.7× 41 0.1× 195 1.6× 154 1.4× 27 0.3× 33 587
Yue Chen China 15 25 0.1× 150 0.5× 261 2.1× 418 3.8× 116 1.1× 67 1.1k
Jinzhong Zhang China 16 37 0.1× 91 0.3× 271 2.2× 227 2.1× 24 0.2× 53 690

Countries citing papers authored by Minghao Piao

Since Specialization
Citations

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

Fields of papers citing papers by Minghao Piao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minghao Piao

This figure shows the co-authorship network connecting the top 25 collaborators of Minghao Piao. A scholar is included among the top collaborators of Minghao Piao 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 Minghao Piao. Minghao Piao 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.
Piao, Minghao, et al.. (2024). Multi-scale guidance diffusion network for wafer map defect recognition. Expert Systems with Applications. 267. 126134–126134. 3 indexed citations
2.
Piao, Minghao, et al.. (2024). Improved wafer map defect pattern classification using automatic data augmentation based lightweight encoder network in contrastive learning. Journal of Intelligent Manufacturing. 36(6). 4129–4141. 2 indexed citations
3.
Huang, Xiaoman, Zhishan Liang, Xiaojie Yang, et al.. (2024). Multilevel Anti-counterfeiting Barcode with Enhanced Information Encryption Based on Stimulus-Responsive Digital Polymers. ACS Applied Materials & Interfaces. 16(33). 43075–43082. 10 indexed citations
4.
Piao, Minghao, et al.. (2023). Image Hash Layer Triggered CNN Framework for Wafer Map Failure Pattern Retrieval and Classification. ACM Transactions on Knowledge Discovery from Data. 18(4). 1–26.
5.
Piao, Minghao, et al.. (2023). Semantic Segmentation-Based Wafer Map Mixed-Type Defect Pattern Recognition. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 42(11). 4065–4074. 11 indexed citations
6.
Piao, Minghao & Cheng Jin. (2023). Analysis of Image Hashing in Wafer Map Failure Pattern Recognition. IEEE Transactions on Semiconductor Manufacturing. 36(3). 378–388. 2 indexed citations
7.
Miao, Tengfei, Yuxin Liu, Lihua Hu, et al.. (2022). Fabrication and Decryption of a Microarray of Digital Dithiosuccinimide Oligomers. Macromolecular Rapid Communications. 43(9). e2200029–e2200029. 11 indexed citations
8.
Piao, Minghao & Cheng Jin. (2022). CNN and ensemble learning based wafer map failure pattern recognition based on local property based features. Journal of Intelligent Manufacturing. 34(8). 3599–3621. 8 indexed citations
9.
Jin, Cheng, et al.. (2020). Wafer map defect pattern classification based on convolutional neural network features and error-correcting output codes. Journal of Intelligent Manufacturing. 31(8). 1861–1875. 49 indexed citations
10.
Piao, Minghao, et al.. (2017). Health Examination Data Based Medical Treatment Prediction by Using SVM. KIPS Transactions on Software and Data Engineering. 6(6). 303–308. 1 indexed citations
11.
Piao, Yongjun, Minghao Piao, & Keun Ho Ryu. (2016). Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles. Computers in Biology and Medicine. 80. 39–44. 38 indexed citations
12.
Piao, Minghao, et al.. (2015). Wind Power Pattern Forecasting Based on Projected Clustering and Classification Methods. ETRI Journal. 37(2). 283–294. 8 indexed citations
13.
Li, Feifei, Minghao Piao, Yongjun Piao, Meijing Li, & Keun Ho Ryu. (2014). A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs. Osong Public Health and Research Perspectives. 5(5). 279–285. 9 indexed citations
14.
Piao, Minghao, et al.. (2014). One pass preprocessing for token-based source code clone detection. 1–6. 3 indexed citations
15.
Piao, Minghao, et al.. (2013). Comparison of Subspace Projection Method with Traditional Clustering Algorithms for Clustering Electricity Consumption Data. 71–76.
16.
Saeed, Khalid, et al.. (2010). IMTAR: Incremental Mining of General Temporal Association Rules. Journal of Information Processing Systems. 6(2). 163–176. 8 indexed citations
17.
Piao, Minghao, et al.. (2009). Emerging Patterns Based Methodology for Prediction of Patients with Myocardial Ischemia. 174–178. 7 indexed citations
18.
Piao, Minghao, et al.. (2008). Classification Methods for Automated Prediction of Power Load Patterns. 한국정보과학회 학술발표논문집. 35. 26–30. 1 indexed citations
19.
20.
Saito, Ikuo, Minghao Piao, & O. Ishihara. (2002). EXTRACTION OF LAND COVERING CHANGES BY LANDSAT TM DATA. Journal of Architecture and Planning (Transactions of AIJ). 67(561). 79–84. 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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