Muhammad Hammad Saleem
- Analytical Chemistry top 1%
- Spectroscopy and Chemometric Analyses 3
- Plant Science top 2%
- Smart Agriculture and AI 10
- Plant Disease Management Techniques 6
- Date Palm Research Studies 4
- Ecology top 10%
- Remote Sensing in Agriculture 2
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- Smart Grid Energy Management 1
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- Smart Grid Security and Resilience 1
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- Vehicle License Plate Recognition 1
- Co-authors
- Johan PotgieterKhalid Mahmood ArifJeha RyuPalaiahnakote ShivakumaraMohamad SaraeeSadaqat Ur RehmanUmapada PalShafiqur Rahman Tito
- Journals
- Expert Systems with Applications (1 paper)IEEE Access (1 paper)Frontiers in Plant Science (2 papers)
- Partner nations
- New ZealandUnited KingdomPakistan
In The Last Decade
Muhammad Hammad Saleem
12 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Analytical Chemistry 341
- Plant Science 1.0k
- Ecology 208
- Drug Discovery 1
- Industrial and Manufacturing Engineering 28
Countries citing papers authored by Muhammad Hammad Saleem
This map shows the geographic impact of Muhammad Hammad Saleem'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 Muhammad Hammad Saleem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Hammad Saleem more than expected).
Fields of papers citing papers by Muhammad Hammad Saleem
This network shows the impact of papers produced by Muhammad Hammad Saleem. 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 Muhammad Hammad Saleem. The network helps show where Muhammad Hammad Saleem may publish in the future.
Co-authorship network
The 10 scholars most cited alongside Muhammad Hammad Saleem, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2022 | 32 | |
| 5 | 2022 | 9 | |
| 6 | 2022 | 28 | |
| 7 | 2022 | 61 | |
| 8 | 2021 | 7 | |
| 9 | Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developmentsbreakdown → | 2021 | 252 |
| 10 | 2020 | 169 | |
| 11 | 2020 | 121 | |
| 12 | Plant Disease Detection and Classification by Deep Learningbreakdown → | 2019 | 496 |
| 13 | 2019 | 6 |
About Muhammad Hammad Saleem
Muhammad Hammad Saleem is a scholar working on Analytical Chemistry, Plant Science and Neurology, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Smart Agriculture and AI (10 papers), Plant Disease Management Techniques (6 papers), Date Palm Research Studies (4 papers), Spectroscopy and Chemometric Analyses (3 papers), Remote Sensing in Agriculture (2 papers), Smart Grid Energy Management (1 paper), Smart Grid Security and Resilience (1 paper) and Vehicle License Plate Recognition (1 paper). The work is most often cited by research in Analytical Chemistry (341 citations), Plant Science (1.0k citations) and Ecology (208 citations). Muhammad Hammad Saleem has collaborated with scholars based in New Zealand, United Kingdom and Pakistan. Frequent co-authors include Johan Potgieter, Khalid Mahmood Arif, Jeha Ryu, Palaiahnakote Shivakumara, Mohamad Saraee, Sadaqat Ur Rehman, Umapada Pal, Shafiqur Rahman Tito, F.H. Hammad and Muhammad Taha. Their work appears in journals such as Expert Systems with Applications, IEEE Access and Frontiers in Plant Science.
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.