Shaoning Pang

2.8k total citations · 1 hit paper
73 papers, 1.7k citations indexed

About

Shaoning Pang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Shaoning Pang has authored 73 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 20 papers in Computer Vision and Pattern Recognition and 13 papers in Molecular Biology. Recurrent topics in Shaoning Pang's work include Face and Expression Recognition (14 papers), Neural Networks and Applications (11 papers) and Machine Learning in Bioinformatics (8 papers). Shaoning Pang is often cited by papers focused on Face and Expression Recognition (14 papers), Neural Networks and Applications (11 papers) and Machine Learning in Bioinformatics (8 papers). Shaoning Pang collaborates with scholars based in New Zealand, Japan and China. Shaoning Pang's co-authors include Nikola Kasabov, Seiichi Ozawa, Sung Yang Bang, Daijin Kim, Hyun‐Chul Kim, Hong-Mo Je, Xuyun Zhang, Tian Wang, Lianyong Qi and Mohammad R. Khosravi and has published in prestigious journals such as ACM Computing Surveys, Pattern Recognition and Information Sciences.

In The Last Decade

Shaoning Pang

72 papers receiving 1.6k 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.

Privacy-Aware Data Fusion and Prediction With Spatial-Temporal Context for Smart City Industrial Environment

2020 201 citations Lianyong Qi, Chunhua Hu et al. IEEE Transactions on Industrial Informatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shaoning Pang New Zealand	18	820	520	215	202	194	73	1.7k
Anca Ralescu United States	19	729 0.9×	384 0.7×	202 0.9×	172 0.9×	237 1.2×	157	1.7k
Mineichi Kudo Japan	18	734 0.9×	611 1.2×	109 0.5×	137 0.7×	238 1.2×	111	1.7k
Ayhan Demiriz Türkiye	11	888 1.1×	550 1.1×	114 0.5×	168 0.8×	148 0.8×	30	1.4k
Zili Zhang China	27	868 1.1×	381 0.7×	165 0.8×	270 1.3×	119 0.6×	119	2.0k
Zne-Jung Lee Taiwan	20	973 1.2×	339 0.7×	317 1.5×	158 0.8×	153 0.8×	73	2.1k
Samira Pouyanfar United States	15	778 0.9×	510 1.0×	179 0.8×	161 0.8×	163 0.8×	28	1.8k
Lin Mei China	24	592 0.7×	642 1.2×	197 0.9×	249 1.2×	144 0.7×	70	1.7k
Nan Zhang China	24	760 0.9×	455 0.9×	163 0.8×	264 1.3×	221 1.1×	155	1.9k
Seth Rogers United States	9	915 1.1×	658 1.3×	139 0.6×	239 1.2×	442 2.3×	13	2.0k

Countries citing papers authored by Shaoning Pang

Since Specialization

Citations

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

Fields of papers citing papers by Shaoning Pang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaoning Pang

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

All Works

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20 of 20 papers shown

Black, Paul, et al.. (2024). A Review of Reinforcement Learning Enabled Autonomous Cyber Operations Platforms. SSRN Electronic Journal. 1 indexed citations

Pang, Shaoning, et al.. (2024). A survey on evaluation of blockchain-based agricultural traceability. Computers and Electronics in Agriculture. 227. 109548–109548. 6 indexed citations

Cao, Yang, et al.. (2022). Auto‐identification of two Sitophilus sibling species on stored wheat using deep convolutional neural network. Pest Management Science. 78(5). 1925–1937. 6 indexed citations

Zhang, Xuyun, Tian Wang, Shaohua Wan, et al.. (2020). Diversified and Scalable Service Recommendation With Accuracy Guarantee. IEEE Transactions on Computational Social Systems. 8(5). 1182–1193. 38 indexed citations

Qi, Lianyong, Chunhua Hu, Xuyun Zhang, et al.. (2020). Privacy-Aware Data Fusion and Prediction With Spatial-Temporal Context for Smart City Industrial Environment. IEEE Transactions on Industrial Informatics. 17(6). 4159–4167. 201 indexed citations breakdown →

Sharifzadeh, Hamid, et al.. (2019). A Comprehensive Review of Computational Methods for Automatic Prediction of Schizophrenia With Insight Into Indigenous Populations. Frontiers in Psychiatry. 10. 659–659. 27 indexed citations

Zhang, Yushu, Jiantao Zhou, Yong Xiang, et al.. (2017). Computation Outsourcing Meets Lossy Channel: Secure Sparse Robustness Decoding Service in Multi-Clouds. IEEE Transactions on Big Data. 1–1. 26 indexed citations

Pang, Shaoning, Lei Zhu, Gang Chen, et al.. (2013). Dynamic class imbalance learning for incremental LPSVM. Neural Networks. 44. 87–100. 22 indexed citations

Narayanan, Ajit, et al.. (2013). The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures. The Scientific World JOURNAL. 2013(1). 671096–671096. 3 indexed citations

10.

Pang, Shaoning. (2012). Image Segmentation Algorithm Based on Grey Relational Analysis and RBF. Jisuanji gongcheng. 1 indexed citations

11.

Pang, Shaoning. (2011). RBF Network Optimization Based on k-means and Quantum Genetic Algorithm. Jisuanji gongcheng. 1 indexed citations

12.

Pang, Shaoning. (2011). Segmentation method of remote sensed images based on principal component analysis and pulse coupled neural network. Computer Engineering and Applications Journal. 1 indexed citations

13.

Pang, Shaoning. (2011). Algorithm for remote sensing image segmentation based on combination of the improved FKCN and local information. Computer Engineering and Applications Journal. 1 indexed citations

14.

Pang, Shaoning. (2010). A new noisy remote image Otsu segmentation algorithm research. Jiguang zazhi. 1 indexed citations

15.

Yang, Jie, et al.. (2010). Remote sensing image thresholding segmentation based on the modified Otsu algorithm. Jiguang zazhi. 31(6). 33–34. 2 indexed citations

16.

Ozawa, Seiichi, Shaoning Pang, & Nikola Kasabov. (2008). Incremental Learning of Chunk Data for Online Pattern Classification Systems. IEEE Transactions on Neural Networks. 19(6). 1061–1074. 80 indexed citations

17.

Hu, Yingjie, Shaoning Pang, & Ilkka Havukkala. (2006). A Novel Microarray Gene Selection Method Based on Consistency. 14–14. 1 indexed citations

18.

Pang, Shaoning, Seiichi Ozawa, & Nikola Kasabov. (2005). Incremental Linear Discriminant Analysis for Classification of Data Streams. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 35(5). 905–914. 248 indexed citations

19.

Ozawa, Seiichi, et al.. (2005). Incremental learning of feature space and classifier for face recognition. Neural Networks. 18(5-6). 575–584. 72 indexed citations

20.

Pang, Shaoning, et al.. (2004). Evolving Computation Offers Potential for Estimation of Pest Establishment.. 5(7). 36–43. 4 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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