Pan Fan

781 total citations · 1 hit paper
11 papers, 574 citations indexed

About

Pan Fan is a scholar working on Plant Science, Biomedical Engineering and Control and Systems Engineering. According to data from OpenAlex, Pan Fan has authored 11 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Plant Science, 3 papers in Biomedical Engineering and 2 papers in Control and Systems Engineering. Recurrent topics in Pan Fan's work include Smart Agriculture and AI (5 papers), Plant Disease Management Techniques (3 papers) and Plant Virus Research Studies (3 papers). Pan Fan is often cited by papers focused on Smart Agriculture and AI (5 papers), Plant Disease Management Techniques (3 papers) and Plant Virus Research Studies (3 papers). Pan Fan collaborates with scholars based in China, United Kingdom and United States. Pan Fan's co-authors include Fuzeng Yang, Zhijie Liu, Bin Yan, Xiaoyan Lei, Meirong Wang, Wang Wang, Heng Liu, D.M. Davies, Qijun Zhao and Renrui Zhang and has published in prestigious journals such as Gut, Remote Sensing and Computers and Electronics in Agriculture.

In The Last Decade

Pan Fan

11 papers receiving 560 citations

Hit Papers

A Real-Time Apple Targets... 2021 2026 2022 2024 2021 100 200 300 400
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.

  1. A Real-Time Apple Targets Detection Method for Picking Robot Based on Improved YOLOv5
    2021 411 citations Bin Yan, Pan Fan et al. Remote Sensing profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pan Fan 316 142 76 75 74 11 574
Bin Yan 313 1.0× 145 1.0× 47 0.6× 74 1.0× 76 1.0× 16 569
Hongjun Wang 445 1.4× 114 0.8× 63 0.8× 111 1.5× 83 1.1× 45 692
Wenxian Feng 297 0.9× 163 1.1× 53 0.7× 72 1.0× 63 0.9× 21 1.2k
Fengyun Wu 406 1.3× 132 0.9× 44 0.6× 114 1.5× 76 1.0× 17 591
Mei Jiang 297 0.9× 153 1.1× 67 0.9× 73 1.0× 69 0.9× 15 572
Jiqing Chen 420 1.3× 114 0.8× 59 0.8× 93 1.2× 51 0.7× 34 598
Hongxing Peng 312 1.0× 78 0.5× 69 0.9× 87 1.2× 56 0.8× 20 455
Kailiang Zhang 531 1.7× 85 0.6× 92 1.2× 143 1.9× 73 1.0× 25 722

Countries citing papers authored by Pan Fan

Since Specialization
Citations

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

Fields of papers citing papers by Pan Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pan Fan

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

All Works

11 of 11 papers shown
1.
Li, Liang, et al.. (2024). Robotic Grasping Technology Integrating Large Kernel Convolution and Residual Connections. Machines. 12(11). 786–786. 1 indexed citations
2.
Fan, Pan, et al.. (2024). Enhanced Real-Time Target Detection for Picking Robots Using Lightweight CenterNet in Complex Orchard Environments. Agriculture. 14(7). 1059–1059. 4 indexed citations
3.
Li, Jian, et al.. (2024). Dynamic Convolution Neural Networks with Both Global and Local Attention for Image Classification. Mathematics. 12(12). 1856–1856. 2 indexed citations
4.
Wang, Meirong, et al.. (2022). Development of a Novel Biomimetic Mechanical Hand Based on Physical Characteristics of Apples. Agriculture. 12(11). 1871–1871. 16 indexed citations
5.
Yan, Bin, Pan Fan, Xiaoyan Lei, Zhijie Liu, & Fuzeng Yang. (2021). A Real-Time Apple Targets Detection Method for Picking Robot Based on Improved YOLOv5. Remote Sensing. 13(9). 1619–1619. 411 indexed citations breakdown →
6.
Fan, Pan, et al.. (2021). A Method of Segmenting Apples Based on Gray-Centered RGB Color Space. Remote Sensing. 13(6). 1211–1211. 30 indexed citations
7.
8.
Fan, Pan, Bin Yan, Meirong Wang, et al.. (2021). Three-finger grasp planning and experimental analysis of picking patterns for robotic apple harvesting. Computers and Electronics in Agriculture. 188. 106353–106353. 39 indexed citations
9.
Liu, Zhijie, et al.. (2021). Gradient Boosting Estimation of the Leaf Area Index of Apple Orchards in UAV Remote Sensing. Remote Sensing. 13(16). 3263–3263. 38 indexed citations
10.
Li, Yafeng, Qijun Zhao, Wenbo Zhang, et al.. (2020). A Simultaneous Cartoon‐Texture Image Segmentation and Image Decomposition Method. Chinese Journal of Electronics. 29(5). 906–915. 5 indexed citations
11.
Ritchie, H D, et al.. (1962). Extracorporeal methods of reducing high blood ammonia levels. Gut. 3(2). 172–176. 5 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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