Fang Mei

799 total citations · 1 hit paper
36 papers, 509 citations indexed

About

Fang Mei is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Fang Mei has authored 36 papers receiving a total of 509 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 11 papers in Electrical and Electronic Engineering and 10 papers in Artificial Intelligence. Recurrent topics in Fang Mei's work include Vehicular Ad Hoc Networks (VANETs) (4 papers), Mobile Ad Hoc Networks (4 papers) and Metaheuristic Optimization Algorithms Research (4 papers). Fang Mei is often cited by papers focused on Vehicular Ad Hoc Networks (VANETs) (4 papers), Mobile Ad Hoc Networks (4 papers) and Metaheuristic Optimization Algorithms Research (4 papers). Fang Mei collaborates with scholars based in China, United States and Canada. Fang Mei's co-authors include Wei Shen, Dan Zeng, Yuanwang Wei, Zhijiang Zhang, Radovan Kovacevic, Yanheng Liu, Guangxue Yue, Xuanjing Shen, Geng Sun and Fang Zheng and has published in prestigious journals such as Expert Systems with Applications, Sensors and IEEE Transactions on Vehicular Technology.

In The Last Decade

Fang Mei

33 papers receiving 485 citations

Hit Papers

align trajectories sort by overperformance

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.

Generative AI for Deep Reinforcement Learning: Framework, Analysis, and Use Cases

2025 15 citations Geng Sun, Dusit Niyato et al. IEEE Wireless Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fang Mei China	12	245	224	129	58	57	36	509
Zhongyi Pei China	5	305 1.2×	481 2.1×	73 0.6×	66 1.1×	25 0.4×	8	856
Ajay J. Joshi United States	11	399 1.6×	443 2.0×	48 0.4×	50 0.9×	19 0.3×	14	738
Liang Jia China	14	179 0.7×	137 0.6×	53 0.4×	36 0.6×	18 0.3×	43	567
Fuyuan Hu China	13	364 1.5×	279 1.2×	23 0.2×	58 1.0×	45 0.8×	68	661
Ahmet Burak Can Türkiye	12	167 0.7×	149 0.7×	176 1.4×	37 0.6×	35 0.6×	43	476
Paweł Ładosz United Kingdom	10	107 0.4×	119 0.5×	103 0.8×	89 1.5×	32 0.6×	17	461
Paulo Martins Engel Brazil	11	167 0.7×	207 0.9×	62 0.5×	50 0.9×	24 0.4×	52	500
Ghodrat Sepidnam Iran	4	67 0.3×	198 0.9×	92 0.7×	60 1.0×	19 0.3×	11	462
Weimin Lei China	12	292 1.2×	72 0.3×	161 1.2×	119 2.1×	13 0.2×	104	617
Jianxi Yang China	14	57 0.2×	192 0.9×	67 0.5×	38 0.7×	19 0.3×	55	644

Countries citing papers authored by Fang Mei

Since Specialization

Citations

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

Fields of papers citing papers by Fang Mei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fang Mei

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

Sun, Geng, Dusit Niyato, Fang Mei, et al.. (2025). Generative AI for Deep Reinforcement Learning: Framework, Analysis, and Use Cases. IEEE Wireless Communications. 32(3). 186–195. 15 indexed citations breakdown →

Sun, Geng, Dusit Niyato, Hongyang Du, et al.. (2025). Generative AI for Game Theory-Based Mobile Networking. IEEE Wireless Communications. 32(1). 122–130. 4 indexed citations

Zhang, Kunpeng, et al.. (2024). Enhancing IoT (Internet of Things) feature selection: A two-stage approach via an improved whale optimization algorithm. Expert Systems with Applications. 256. 124936–124936. 5 indexed citations

Zhang, Kunpeng, Yanheng Liu, Xue Wang, et al.. (2024). IBMRFO: Improved binary manta ray foraging optimization with chaotic tent map and adaptive somersault factor for feature selection. Expert Systems with Applications. 251. 123977–123977. 13 indexed citations

Zhang, Kunpeng, Yanheng Liu, Fang Mei, Jingyi Jin, & Yiming Wang. (2023). Boost Correlation Features with 3D-MiIoU-Based Camera-LiDAR Fusion for MODT in Autonomous Driving. Remote Sensing. 15(4). 874–874. 11 indexed citations

Zhang, Kunpeng, Yanheng Liu, Fang Mei, Geng Sun, & Jingyi Jin. (2023). IBGJO: Improved Binary Golden Jackal Optimization with Chaotic Tent Map and Cosine Similarity for Feature Selection. Entropy. 25(8). 1128–1128. 13 indexed citations

Mei, Fang, et al.. (2023). How does the bond market price corporate ESG engagement? Evidence from China. Economic Analysis and Policy. 78. 1406–1423. 12 indexed citations

Mei, Fang, et al.. (2023). A Multi-objective Optimization Approach for Secure Communications Based on Collaborative Beamforming in UAV Networks. 1–6. 2 indexed citations

Lang, Ping, Jian Wang, Fang Mei, & Weiwen Deng. (2019). A vehicle's weight‐based prioritized reciprocity MAC. Transactions on Emerging Telecommunications Technologies. 30(12). 5 indexed citations

10.

Mei, Fang, et al.. (2019). Copy-Move Forgery Detection Based on Interest Point and Local Search Algorithm. 207–211. 1 indexed citations

11.

Wang, Jian, Qiang Zheng, Fang Mei, Weiwen Deng, & Yuming Ge. (2019). A Novel Method to Enable the Awareness Ability of Non-V2V-Equipped Vehicles in Vehicular Networks. Sensors. 19(9). 2187–2187. 2 indexed citations

12.

Qin, Jun, Xuanjing Shen, Fang Mei, & Fang Zheng. (2018). An Otsu multi-thresholds segmentation algorithm based on improved ACO. The Journal of Supercomputing. 75(2). 955–967. 40 indexed citations

13.

Mei, Fang, et al.. (2015). The Evaluation of Teaching Level and Exploration of Improving Ability for Young Teachers in Higher Education. Creative Education. 6(10). 976–981.

14.

Mei, Fang, Guangxue Yue, & Qi Yu. (2014). The Study on An Application of Otsu Method in Canny Operator. 30 indexed citations

15.

Yue, Guangxue, et al.. (2009). The Mathematical Model and Applications of Coded Structured Light System for Object Detecting. Journal of Computers. 4(1). 6 indexed citations

16.

Mei, Fang. (2008). Application of Otsu thresholding method on Canny operator. Jisuanji gongcheng yu sheji. 10 indexed citations

17.

Zhao, Yue, et al.. (2008). A Method for Mobile Path Prediction Based on Data Mining. 40. 691–695. 2 indexed citations

18.

Li, Yue, et al.. (2006). Three dimensional modeling of the working linkage of load-haul-dump loader. The International Journal of Advanced Manufacturing Technology. 32(9-10). 856–862. 1 indexed citations

19.

Mei, Fang. (2005). Algorithms for B-spline Surface Skinning. 2 indexed citations

20.

Kovacevic, Radovan & Fang Mei. (1994). Modeling of the influence of the abrasive waterjet cutting parameters on the depth of cut based on fuzzy rules. International Journal of Machine Tools and Manufacture. 34(1). 55–72. 37 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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