Md Sultan Mahmud

1.1k total citations · 1 hit paper
29 papers, 751 citations indexed

About

Md Sultan Mahmud is a scholar working on Plant Science, Environmental Engineering and Ecology. According to data from OpenAlex, Md Sultan Mahmud has authored 29 papers receiving a total of 751 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Plant Science, 7 papers in Environmental Engineering and 6 papers in Ecology. Recurrent topics in Md Sultan Mahmud's work include Plant Surface Properties and Treatments (10 papers), Smart Agriculture and AI (10 papers) and Remote Sensing and LiDAR Applications (7 papers). Md Sultan Mahmud is often cited by papers focused on Plant Surface Properties and Treatments (10 papers), Smart Agriculture and AI (10 papers) and Remote Sensing and LiDAR Applications (7 papers). Md Sultan Mahmud collaborates with scholars based in United States, Canada and Pakistan. Md Sultan Mahmud's co-authors include Young Chang, Jaemyung Shin, Tanzeel U. Rehman, Azlan Zahid, Jian Jin, Long He, Daeun Choi, Paul Heinemann, Anup Das and James R. Schupp and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Computers and Electronics in Agriculture.

In The Last Decade

Md Sultan Mahmud

28 papers receiving 725 citations

Hit Papers

Current and future applications of statistical machine le... 2018 2026 2020 2023 2018 50 100 150 200 250
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. Current and future applications of statistical machine learning algorithms for agricultural machine vision systems
    2018 294 citations Tanzeel U. Rehman, Md Sultan Mahmud et al. Computers and Electronics in Agriculture profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Md Sultan Mahmud United States 12 539 145 127 99 79 29 751
D. Stajnko Slovenia 14 575 1.1× 142 1.0× 166 1.3× 128 1.3× 59 0.7× 55 804
Hao Gan United States 14 563 1.0× 149 1.0× 198 1.6× 61 0.6× 64 0.8× 44 928
A. Subeesh India 14 550 1.0× 126 0.9× 141 1.1× 93 0.9× 75 0.9× 35 862
Yadong Liu China 11 526 1.0× 229 1.6× 121 1.0× 134 1.4× 40 0.5× 20 860
Sierra Young United States 13 530 1.0× 200 1.4× 143 1.1× 70 0.7× 33 0.4× 39 786
Xinhua Wei China 13 601 1.1× 178 1.2× 133 1.0× 55 0.6× 52 0.7× 31 915
Young Chang Canada 18 768 1.4× 220 1.5× 240 1.9× 96 1.0× 88 1.1× 51 1.1k
Daeun Choi United States 15 478 0.9× 91 0.6× 73 0.6× 110 1.1× 27 0.3× 43 623
Long He United States 19 761 1.4× 143 1.0× 122 1.0× 158 1.6× 38 0.5× 68 996
Zhihua Diao China 12 428 0.8× 104 0.7× 160 1.3× 68 0.7× 40 0.5× 33 645

Countries citing papers authored by Md Sultan Mahmud

Since Specialization
Citations

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

Fields of papers citing papers by Md Sultan Mahmud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Md Sultan Mahmud. 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 Md Sultan Mahmud. The network helps show where Md Sultan Mahmud may publish in the future.

Co-authorship network of co-authors of Md Sultan Mahmud

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

All Works

20 of 20 papers shown
1.
Asif, Muhammad, et al.. (2025). Technological Progress Toward Peanut Disease Management: A Review. Sensors. 25(4). 1255–1255. 2 indexed citations
2.
Mahmud, Md Sultan, et al.. (2025). 3D sensing and perception for precision weed management: a review of modalities, reconstruction pipelines, and context-aware detection. Computers and Electronics in Agriculture. 240. 111219–111219. 1 indexed citations
3.
Mahmud, Md Sultan, et al.. (2024). Measuring ornamental tree canopy attributes for precision spraying using drone technology and self-supervised segmentation. Computers and Electronics in Agriculture. 225. 109359–109359. 6 indexed citations
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Mahmud, Md Sultan, Azlan Zahid, & Anup Das. (2023). Sensing and Automation Technologies for Ornamental Nursery Crop Production: Current Status and Future Prospects. Sensors. 23(4). 1818–1818. 13 indexed citations
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Shin, Jaemyung, et al.. (2022). Trends and Prospect of Machine Vision Technology for Stresses and Diseases Detection in Precision Agriculture. AgriEngineering. 5(1). 20–39. 34 indexed citations
9.
Mahmud, Md Sultan, Azlan Zahid, Long He, et al.. (2022). Development of an Automatic Airflow Control System for Precision Sprayers Based on Tree Canopy Density. Journal of the ASABE. 65(6). 1225–1240. 6 indexed citations
10.
Mahmud, Md Sultan, Long He, Paul Heinemann, Daeun Choi, & Heping Zhu. (2022). Unmanned aerial vehicle based tree canopy characteristics measurement for precision spray applications. SHILAP Revista de lepidopterología. 4. 100153–100153. 19 indexed citations
11.
Khan, Muhammad Usman, Usman Amin, Md Sultan Mahmud, et al.. (2021). Development, Fabrication and Performance Evaluation of Mango Pulp Extractor for Cottage Industry. AgriEngineering. 3(4). 827–839. 2 indexed citations
12.
Mahmud, Md Sultan, et al.. (2021). Opportunities and Possibilities of Developing an Advanced Precision Spraying System for Tree Fruits. Sensors. 21(9). 3262–3262. 35 indexed citations
13.
Mahmud, Md Sultan, Azlan Zahid, Anup Das, Muhammad Muzammil, & Muhammad Usman Khan. (2021). A systematic literature review on deep learning applications for precision cattle farming. Computers and Electronics in Agriculture. 187. 106313–106313. 79 indexed citations
14.
Zahid, Azlan, Md Sultan Mahmud, & Long He. (2021). Evaluation of Branch Cutting Torque Requirements Intended for Robotic Apple Tree Pruning. 5 indexed citations
15.
Mahmud, Md Sultan, Azlan Zahid, Long He, et al.. (2021). LiDAR-sensed tree canopy correction in uneven terrain conditions using a sensor fusion approach for precision sprayers. Computers and Electronics in Agriculture. 191. 106565–106565. 9 indexed citations
16.
Zahid, Azlan, Md Sultan Mahmud, Long He, et al.. (2021). Technological advancements towards developing a robotic pruner for apple trees: A review. Computers and Electronics in Agriculture. 189. 106383–106383. 66 indexed citations
17.
Mahmud, Md Sultan, Qamar U. Zaman, Travis J. Esau, et al.. (2020). Real-Time Detection of Strawberry Powdery Mildew Disease Using a Mobile Machine Vision System. Agronomy. 10(7). 1027–1027. 24 indexed citations
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Mahmud, Md Sultan, Qamar U. Zaman, Travis J. Esau, G.W. Price, & Balakrishnan Prithiviraj. (2019). Development of an artificial cloud lighting condition system using machine vision for strawberry powdery mildew disease detection. Computers and Electronics in Agriculture. 158. 219–225. 28 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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