Man Cheng

425 total citations · 1 hit paper
11 papers, 304 citations indexed

About

Man Cheng is a scholar working on Plant Science, Computer Vision and Pattern Recognition and Ecology. According to data from OpenAlex, Man Cheng has authored 11 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Plant Science, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Ecology. Recurrent topics in Man Cheng's work include Smart Agriculture and AI (5 papers), Date Palm Research Studies (3 papers) and Greenhouse Technology and Climate Control (2 papers). Man Cheng is often cited by papers focused on Smart Agriculture and AI (5 papers), Date Palm Research Studies (3 papers) and Greenhouse Technology and Climate Control (2 papers). Man Cheng collaborates with scholars based in China. Man Cheng's co-authors include Zhenjiang Cai, Hongbo Yuan, Qifan Wang, Shuo Huang, Qifan Wang, Hongbo Yuan, Yueqin Liu, Jinlin Zhang, Sheng Du and Nan Wang and has published in prestigious journals such as Environmental Pollution, Frontiers in Plant Science and Computers and Electronics in Agriculture.

In The Last Decade

Man Cheng

9 papers receiving 296 citations

Hit Papers

align trajectories

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.

A deep learning approach incorporating YOLO v5 and attention mechanisms for field real-time detection of the invasive weed Solanum rostratum Dunal seedlings

2022 143 citations Qifan Wang, Man Cheng et al. Computers and Electronics in Agriculture profile →

Peers

Man Cheng

PS

ECOLO

CVPR

AC

FS

Ron Berenstein Israel

Anil Bhujel South Korea

Md Nasim Reza South Korea

Ye Mu China

Dan Jeric Arcega Rustia Taiwan

Adair da Silva Oliveira Brazil

Jiong Mu China

Xinliang Tian China

Luciano Vieira Koenigkan Brazil

Jinglei Tang China

Ron Berenstein Israel

Man Cheng

266 ×1.4

PS

55 ×0.8

ECOLO

59 ×1.4

CVPR

33 ×0.9

AC

43 ×1.5

FS

Citations per year, relative to Man Cheng Man Cheng (= 1×) peers Ron Berenstein

Countries citing papers authored by Man Cheng

Since Specialization

Citations

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

Fields of papers citing papers by Man Cheng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Man Cheng

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

Yuan, Hongbo, et al.. (2025). Sheep identification based on face features with the method and practical application analysis. Smart Agricultural Technology. 12. 101362–101362.

2.

Du, Sheng, Yanfang Yang, Hongbo Yuan, & Man Cheng. (2025). Application of deep learning for real-time detection, localization, and counting of the malignant invasive weed Solanum rostratum Dunal. Frontiers in Plant Science. 15. 1486929–1486929. 3 indexed citations

3.

Zhang, Jiake, Zi Ye, Lieyang Fan, et al.. (2024). miR-629-3p inhibits fine particulate matter exposure-induced lung function decline: Results from the two-stage population study and in vitro study. Environmental Pollution. 367. 125535–125535. 1 indexed citations

4.

Yuan, Hongbo, et al.. (2023). A Method to Estimate Evapotranspiration in Greenhouse Conditions by Artificial Neural Networks Using Limited Climate Parameters. Journal of Physics Conference Series. 2650(1). 12029–12029. 1 indexed citations

5.

Yuan, Hongbo, et al.. (2022). An Improved DeepLab v3+ Deep Learning Network Applied to the Segmentation of Grape Leaf Black Rot Spots. Frontiers in Plant Science. 13. 795410–795410. 49 indexed citations

6.

Wang, Qifan, et al.. (2022). A deep learning approach incorporating YOLO v5 and attention mechanisms for field real-time detection of the invasive weed Solanum rostratum Dunal seedlings. Computers and Electronics in Agriculture. 199. 107194–107194. 143 indexed citations breakdown →

7.

Cheng, Man, et al.. (2022). Application of deep learning in sheep behaviors recognition and influence analysis of training data characteristics on the recognition effect. Computers and Electronics in Agriculture. 198. 107010–107010. 42 indexed citations

8.

Cheng, Man, et al.. (2021). Grape Leaf Black Rot Detection Based on Super-Resolution Image Enhancement and Deep Learning. Frontiers in Plant Science. 12. 695749–695749. 30 indexed citations

9.

Wang, Qifan, et al.. (2021). An image segmentation method based on deep learning for damage assessment of the invasive weed Solanum rostratum Dunal. Computers and Electronics in Agriculture. 188. 106320–106320. 32 indexed citations

10.

Wang, Nan, et al.. (2014). Development of a Machine Vision System for Solar Wafer Counting. TELKOMNIKA Indonesian Journal of Electrical Engineering. 12(5). 2 indexed citations

11.

Cheng, Man, et al.. (2012). The design of greenhouse environment detection system based on solar-powered. World Automation Congress. 1–4. 1 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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