Minne Li

772 total citations
11 papers, 276 citations indexed

About

Minne Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Nature and Landscape Conservation. According to data from OpenAlex, Minne Li has authored 11 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Nature and Landscape Conservation. Recurrent topics in Minne Li's work include Fish Ecology and Management Studies (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper) and Game Theory and Applications (1 paper). Minne Li is often cited by papers focused on Fish Ecology and Management Studies (2 papers), Generative Adversarial Networks and Image Synthesis (1 paper) and Game Theory and Applications (1 paper). Minne Li collaborates with scholars based in China, United Kingdom and United States. Minne Li's co-authors include Yaodong Yang, Guobin Wu, Jun Wang, Zhiwei Qin, Jieping Ye, Yan Jiao, Chenxi Wang, Weinan Zhang, Rui Luo and Ming Zhou and has published in prestigious journals such as Neural Networks, Frontiers in Physiology and Animals.

In The Last Decade

Minne Li

9 papers receiving 265 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Minne Li China	5	132	77	66	55	45	11	276
Dingyuan Shi China	9	84 0.6×	126 1.6×	35 0.5×	19 0.3×	27 0.6×	20	298
Laurent Moalic France	9	55 0.4×	28 0.4×	131 2.0×	13 0.2×	9 0.2×	28	283
Daniel Ayala Spain	8	150 1.1×	56 0.7×	101 1.5×	46 0.8×	10 0.2×	26	298
Yinuo Zhao China	7	48 0.4×	87 1.1×	49 0.7×	18 0.3×	3 0.1×	12	299
Yanhua Li China	5	41 0.3×	22 0.3×	147 2.2×	68 1.2×	5 0.1×	14	280
Eduard Zadobrischi Romania	10	53 0.4×	14 0.2×	20 0.3×	29 0.5×	6 0.1×	32	239
Zipeng Dai China	10	46 0.3×	72 0.9×	66 1.0×	16 0.3×	3 0.1×	13	368
Zhihan Fang United States	11	92 0.7×	45 0.6×	142 2.2×	10 0.2×	7 0.2×	25	340
Haotian Wang China	7	75 0.6×	31 0.4×	23 0.3×	8 0.1×	7 0.2×	37	222
Wei Chang United States	8	16 0.1×	46 0.6×	38 0.6×	13 0.2×	8 0.2×	34	209

Countries citing papers authored by Minne Li

Since Specialization

Citations

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

Fields of papers citing papers by Minne Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minne Li

This figure shows the co-authorship network connecting the top 25 collaborators of Minne Li. A scholar is included among the top collaborators of Minne Li 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 Minne Li. Minne Li 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:

11 of 11 papers shown

1.

Jian, Songlei, et al.. (2024). A unified multimodal classification framework based on deep metric learning. Neural Networks. 181. 106747–106747. 2 indexed citations

2.

Cai, Lü, David Johnson, Minne Li, et al.. (2023). Swimming ability of cyprinid species (subfamily schizothoracinae) at high altitude. Frontiers in Physiology. 14. 1152697–1152697. 2 indexed citations

3.

Li, Minne, et al.. (2023). Swarm GAN: Stabilizing Training of Generative Adversarial Networks via Swarm Intelligence. 171–177. 2 indexed citations

4.

Li, Minne, Ruidong An, Min Chen, & Jia Li. (2022). Evaluation of Volitional Swimming Behavior of Schizothorax prenanti Using an Open-Channel Flume with Spatially Heterogeneous Turbulent Flow. Animals. 12(6). 752–752. 13 indexed citations

5.

Zhang, Haifeng, Weizhe Chen, Minne Li, et al.. (2020). Bi-Level Actor-Critic for Multi-Agent Coordination. Proceedings of the AAAI Conference on Artificial Intelligence. 34(5). 7325–7332. 42 indexed citations

6.

Li, Minne, et al.. (2019). Optimizing Object-based Perception and Control by Free-Energy Principle.. arXiv (Cornell University).

7.

Li, Minne, Zhiwei Qin, Yan Jiao, et al.. (2019). Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning. 983–994. 163 indexed citations

8.

Yang, Yaodong, Rui Luo, Minne Li, et al.. (2018). Mean Field Multi-Agent Reinforcement Learning. UCL Discovery (University College London). 5571–5580. 45 indexed citations

9.

Chen, Xinyuan, Zhaoning Zhang, Minne Li, & Dongsheng Li. (2018). Border-oriented post-processing refinement on detected vehicle bounding box for ADAS. 243–243.

10.

Zhang, Chengfei, et al.. (2016). SMARTPARTITION: Efficient Partitioning for Natural Graphs. 3 1. 130–131. 1 indexed citations

11.

Zhao, Yunxiang, et al.. (2016). Pegasus: a distributed and load-balancing fingerprint identification system. Frontiers of Information Technology & Electronic Engineering. 17(8). 766–780. 6 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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