Cheng Hu

674 total citations
27 papers, 383 citations indexed

About

Cheng Hu is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Mechanical Engineering. According to data from OpenAlex, Cheng Hu has authored 27 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 7 papers in Cellular and Molecular Neuroscience and 6 papers in Mechanical Engineering. Recurrent topics in Cheng Hu's work include CCD and CMOS Imaging Sensors (6 papers), Advanced Memory and Neural Computing (6 papers) and Modular Robots and Swarm Intelligence (5 papers). Cheng Hu is often cited by papers focused on CCD and CMOS Imaging Sensors (6 papers), Advanced Memory and Neural Computing (6 papers) and Modular Robots and Swarm Intelligence (5 papers). Cheng Hu collaborates with scholars based in China, United Kingdom and Taiwan. Cheng Hu's co-authors include Shigang Yue, Qinbing Fu, Hsing I. Chen, Hongxin Wang, Farshad Arvin, Jigen Peng, Caihua Xiong, F. Claire Rind, Jigen Peng and Tian Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and American Journal of Physiology-Heart and Circulatory Physiology.

In The Last Decade

Cheng Hu

26 papers receiving 374 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cheng Hu China	12	127	113	108	97	72	27	383
Mario I. Chacón-Murguía Mexico	11	176 1.4×	74 0.7×	96 0.9×	293 3.0×	19 0.3×	58	591
Fangwen Yu China	8	91 0.7×	39 0.3×	185 1.7×	88 0.9×	85 1.2×	22	342
Marco Guermandi Italy	15	145 1.1×	109 1.0×	271 2.5×	31 0.3×	15 0.2×	28	536
Rahul Upadhyay India	12	260 2.0×	40 0.4×	56 0.5×	32 0.3×	28 0.4×	49	432
Jigang Tong China	12	83 0.7×	38 0.3×	65 0.6×	73 0.8×	23 0.3×	53	289
F. Javier Toledo Spain	12	52 0.4×	29 0.3×	70 0.6×	79 0.8×	28 0.4×	36	297
Yatindra Kumar India	10	526 4.1×	82 0.7×	110 1.0×	60 0.6×	84 1.2×	20	737
Chuangquan Chen China	13	238 1.9×	39 0.3×	60 0.6×	57 0.6×	18 0.3×	31	446
Yi Xia China	12	181 1.4×	57 0.5×	74 0.7×	72 0.7×	17 0.2×	30	392
Ajat Shatru Arora India	14	112 0.9×	55 0.5×	17 0.2×	86 0.9×	14 0.2×	62	482

Countries citing papers authored by Cheng Hu

Since Specialization

Citations

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

Fields of papers citing papers by Cheng Hu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cheng Hu

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

Dong, Zihang, et al.. (2025). Optimal energy management of buildings using neural network-based thermal prediction and economic model predictive control. Advanced Engineering Informatics. 71. 104278–104278.

Wang, Rui, et al.. (2024). An adaptive OS-CFAR detector for dynamic group targets. IET conference proceedings.. 2023(47). 1600–1605. 1 indexed citations

Gao, Qian, et al.. (2024). Study on Structural Design and Motion Characteristics of Magnetic Helical Soft Microrobots with Drug-Carrying Function. Micromachines. 15(6). 731–731. 1 indexed citations

He, Yifeng, Barry Lennox, Cheng Hu, & Farshad Arvin. (2024). Bubbles-Swarm Micro Surface Robots for Underwater Inspection. Research Explorer (The University of Manchester). 305–310. 1 indexed citations

Chen, Hao, et al.. (2024). Unveiling the power of Haar frequency domain: Advancing small target motion detection in dim light. Applied Soft Computing. 167. 112281–112281. 1 indexed citations

Wang, Hongxin, et al.. (2022). Attention and Prediction-Guided Motion Detection for Low-Contrast Small Moving Targets. IEEE Transactions on Cybernetics. 53(10). 6340–6352. 14 indexed citations

Fu, Qinbing, et al.. (2021). Robustness of Bio-Inspired Visual Systems for Collision Prediction in Critical Robot Traffic. Frontiers in Robotics and AI. 8. 529872–529872. 8 indexed citations

Liu, Tian, et al.. (2021). A Versatile Vision-Pheromone-Communication Platform for Swarm Robotics. Lincoln Repository (University of Lincoln). 4 indexed citations

Wang, Hongxin, et al.. (2021). Enhancing LGMD’s Looming Selectivity for UAV With Spatial–Temporal Distributed Presynaptic Connections. IEEE Transactions on Neural Networks and Learning Systems. 34(5). 2539–2553. 19 indexed citations

10.

Hu, Cheng, et al.. (2021). A Multiple Pheromone Communication System for Swarm Intelligence. IEEE Access. 9. 148721–148737. 6 indexed citations

11.

Liu, Tian, et al.. (2019). ColCOS Φ: A Multiple Pheromone Communication System for Swarm Robotics and Social Insects Research. 59–66. 10 indexed citations

12.

Liu, Yujun, Cheng Hu, & Yi Hong. (2019). Electric Energy Substitution Potential Prediction Based on Logistic Curve Fitting and Improved BP Neural Network Algorithm. Elektronika ir Elektrotechnika. 25(3). 18–24. 11 indexed citations

13.

Fu, Qinbing, Cheng Hu, Jigen Peng, F. Claire Rind, & Shigang Yue. (2019). A Robust Collision Perception Visual Neural Network With Specific Selectivity to Darker Objects. IEEE Transactions on Cybernetics. 50(12). 5074–5088. 43 indexed citations

14.

Fu, Qinbing, Cheng Hu, Jigen Peng, & Shigang Yue. (2018). Shaping the collision selectivity in a looming sensitive neuron model with parallel ON and OFF pathways and spike frequency adaptation. Neural Networks. 106. 127–143. 32 indexed citations

15.

Fu, Qinbing, Cheng Hu, Pengcheng Liu, & Shigang Yue. (2018). Towards Computational Models of Insect Motion Detectors for Robot Vision. Lincoln Repository (University of Lincoln). 8 indexed citations

16.

Fu, Qinbing, Cheng Hu, Tian Liu, & Shigang Yue. (2017). Collision selective LGMDs neuron models research benefits from a vision-based autonomous micro robot. Lincoln Repository (University of Lincoln). 3996–4002. 20 indexed citations

17.

Hu, Cheng, Farshad Arvin, Caihua Xiong, & Shigang Yue. (2016). Bio-Inspired Embedded Vision System for Autonomous Micro-Robots: The LGMD Case. IEEE Transactions on Cognitive and Developmental Systems. 9(3). 241–254. 46 indexed citations

18.

Hu, Cheng, Farshad Arvin, & Shigang Yue. (2014). Development of a bio-inspired vision system for mobile micro-robots. Research Explorer (The University of Manchester). 81–86. 9 indexed citations

19.

Chen, Hsing I. & Cheng Hu. (1997). Endogenous nitric oxide on arterial hemodynamics: a comparison between normotensive and hypertensive rats. American Journal of Physiology-Heart and Circulatory Physiology. 273(4). H1816–H1823. 40 indexed citations

20.

Hu, Cheng, et al.. (1994). The correlation of cardiac mass with arterial haemodynamics of resistive and capacitive load in rats with normotension and established hypertension. Pflügers Archiv - European Journal of Physiology. 428(5-6). 533–541. 17 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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