Liyun Gong

531 total citations
22 papers, 339 citations indexed

About

Liyun Gong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Plant Science. According to data from OpenAlex, Liyun Gong has authored 22 papers receiving a total of 339 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 4 papers in Plant Science. Recurrent topics in Liyun Gong's work include Greenhouse Technology and Climate Control (4 papers), Human Pose and Action Recognition (4 papers) and Video Surveillance and Tracking Methods (4 papers). Liyun Gong is often cited by papers focused on Greenhouse Technology and Climate Control (4 papers), Human Pose and Action Recognition (4 papers) and Video Surveillance and Tracking Methods (4 papers). Liyun Gong collaborates with scholars based in United Kingdom, China and India. Liyun Gong's co-authors include Miao Yu, Stefanos Kollias, Simon Pearson, Vassilis Cutsuridis, Shouyong Jiang, Asoke K. Nandi, Hyondong Oh, Wen‐Hua Chen, Rui Fa and Jonathon A. Chambers and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Liyun Gong

21 papers receiving 324 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Liyun Gong United Kingdom	10	88	88	70	48	41	22	339
Amani Abdulrahman Albraikan Saudi Arabia	13	47 0.5×	62 0.7×	80 1.1×	67 1.4×	18 0.4×	29	363
Sanam Narejo Pakistan	11	138 1.6×	54 0.6×	111 1.6×	59 1.2×	45 1.1×	42	434
Moataz M. Abdelwahab Egypt	10	259 2.9×	118 1.3×	56 0.8×	15 0.3×	34 0.8×	45	502
Yifei Chen China	8	97 1.1×	50 0.6×	45 0.6×	23 0.5×	25 0.6×	24	367
Habib Khan South Korea	10	113 1.3×	57 0.6×	52 0.7×	18 0.4×	14 0.3×	15	329
R Meghana India	4	115 1.3×	39 0.4×	73 1.0×	14 0.3×	22 0.5×	6	350
G Divya India	3	98 1.1×	38 0.4×	68 1.0×	14 0.3×	24 0.6×	6	327
Dong-Youn Kim South Korea	9	62 0.7×	61 0.7×	24 0.3×	29 0.6×	22 0.5×	41	300
Mighty Abra Ayidzoe Ghana	7	131 1.5×	77 0.9×	141 2.0×	17 0.4×	21 0.5×	17	422

Countries citing papers authored by Liyun Gong

Since Specialization

Citations

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

Fields of papers citing papers by Liyun Gong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liyun Gong

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

Leung, Clement H. C., et al.. (2025). Privacy-Preserving Abnormal Gait Detection Using Computer Vision and Machine Learning. EAI Endorsed Transactions on Pervasive Health and Technology. 11.

Gong, Liyun, et al.. (2024). Computer Vision Based Transfer Learning-Aided Transformer Model for Fall Detection and Prediction. IEEE Access. 12. 28798–28809. 10 indexed citations

Gong, Liyun, Miao Yu, & Stefanos Kollias. (2023). Optimizing Crop Yield and Reducing Energy Consumption in Greenhouse Control Using PSO-MPC Algorithm. Algorithms. 16(5). 243–243. 9 indexed citations

Gong, Liyun, et al.. (2023). Enhancing privacy with optical element design for fall detection. Electronics Letters. 59(20). 2 indexed citations

Gong, Liyun, Miao Yu, Vassilis Cutsuridis, Stefanos Kollias, & Simon Pearson. (2022). A Novel Model Fusion Approach for Greenhouse Crop Yield Prediction. Horticulturae. 9(1). 5–5. 9 indexed citations

Gong, Liyun, Lu Zhang, Ming Zhu, et al.. (2021). A novel computer vision-based data driven modelling approach for person specific fall detection. Journal of Ambient Intelligence and Smart Environments. 13(5). 373–387. 3 indexed citations

Gong, Liyun, Miao Yu, Shouyong Jiang, et al.. (2021). Studies of evolutionary algorithms for the reduced Tomgro model calibration for modelling tomato yields. SHILAP Revista de lepidopterología. 1. 100011–100011. 8 indexed citations

Gong, Liyun, Miao Yu, Shouyong Jiang, Vassilis Cutsuridis, & Simon Pearson. (2021). Deep Learning Based Prediction on Greenhouse Crop Yield Combined TCN and RNN. Sensors. 21(13). 4537–4537. 81 indexed citations

Gong, Liyun, Miao Yu, Wenting Duan, et al.. (2020). A novel unified deep neural networks methodology for use by date recognition in retail food package image. Signal Image and Video Processing. 15(3). 449–457. 15 indexed citations

10.

Gong, Liyun, Francesco Calivá, Mark Swainson, et al.. (2018). An End-to-End Deep Neural Architecture for Optical Character Verification and Recognition in Retail Food Packaging. Lincoln Repository (University of Lincoln). 2376–2380. 19 indexed citations

11.

Gong, Liyun & Miao Yu. (2018). A new Gaussian mixture method with exactly exploiting the negative information for GMTI radar tracking in a low-observable environment. Aerospace Science and Technology. 80. 1–10. 7 indexed citations

12.

Gong, Liyun, Tingting Mu, Meng Wang, Hengchang Liu, & John Y. Goulermas. (2017). Evolutionary nonnegative matrix factorization with adaptive control of cluster quality. Neurocomputing. 272. 237–249. 4 indexed citations

13.

Gong, Liyun, Miao Yu, & Timothy Gordon. (2017). Online codebook modeling based background subtraction with a moving camera. 136–140. 5 indexed citations

14.

Gong, Liyun & Miao Yu. (2017). A new interacting multiple model particle filter based ballistic missile tracking method. Lincoln Repository (University of Lincoln). 81–85. 1 indexed citations

15.

Yu, Miao, Liyun Gong, Hyondong Oh, Wen‐Hua Chen, & Jonathon A. Chambers. (2017). Multiple Model Ballistic Missile Tracking With State-Dependent Transitions and Gaussian Particle Filtering. IEEE Transactions on Aerospace and Electronic Systems. 54(3). 1066–1081. 37 indexed citations

16.

Gong, Liyun & Asoke K. Nandi. (2013). Clustering By Non-Negative Matrix Factorization With Independent Principal Component Initialization. Lincoln Repository (University of Lincoln). 1–5. 2 indexed citations

17.

Gong, Liyun & Asoke K. Nandi. (2013). An enhanced initialization method for non-negative matrix factorization. Lincoln Repository (University of Lincoln). 13. 1–6. 10 indexed citations

18.

Cong, Fengyu, Vinoo Alluri, Asoke K. Nandi, et al.. (2013). Linking Brain Responses to Naturalistic Music Through Analysis of Ongoing EEG and Stimulus Features. IEEE Transactions on Multimedia. 15(5). 1060–1069. 49 indexed citations

19.

Fa, Rui, Asoke K. Nandi, & Liyun Gong. (2012). Clustering analysis for gene expression data: A methodological review. Lincoln Repository (University of Lincoln). 2005. 1–6. 7 indexed citations

20.

Gong, Liyun, Richard K. Burdick, & Jorge Quiroz. (2005). Confidence Intervals for Unbalanced Two-factor Gauge R&R Studies. Quality and Reliability Engineering International. 21(8). 727–741. 12 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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