Muhammad Imran Ahmad

657 citations
48 papers · 434 indexed · h-index 8

Muhammad Imran Ahmad

37 papers receiving 406 citations

Peers

Muhammad Imran Ahmad
Comparison fields: 5 of 79
  • Signal Processing 110
  • Global and Planetary Change 164
  • Computer Vision and Pattern Recognition 104
  • Statistics and Probability 38
  • Water Science and Technology 62
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Mihoko Minami Japan
Md. Khademul Islam Molla Japan
Manli Zhu United States
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Ehsan Lotfi Iran
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Citations per year

Countries citing papers authored by Muhammad Imran Ahmad

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Imran Ahmad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Imran Ahmad. 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 Imran Ahmad. The network helps show where Muhammad Imran Ahmad may publish in the future.

Co-authorship network

The 24 scholars most cited alongside Muhammad Imran Ahmad, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Muhammad Imran Ahmad Line = papers co-authored together Muhammad Imran Ahmad links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20250
4 20250
5 20241
6 20242
7 20235
8 20215
9 20215
10 20216
11 20192
12 20193
13 20170
14
A Survey of Iris Recognition System
20161
15
Palmprint Recognition Using Different Level of Information Fusion
20160
16
Palmprint Recognition using Principle Component Analysis Implemented on TMS320C6713 DSP Processor
20161
17
Gait Feature Extraction and Recognition in Biometric System
20160
18
Palmprint recognition using local and global features
20142
19 20141
20 20091

About Muhammad Imran Ahmad

Muhammad Imran Ahmad is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Media Technology, having authored 48 papers that have together received 434 indexed citations. Recurring topics across this work include Biometric Identification and Security (19 papers), Face and Expression Recognition (13 papers), Face recognition and analysis (11 papers), Smart Agriculture and AI (5 papers), Advanced Data Compression Techniques (4 papers), Image Retrieval and Classification Techniques (4 papers), Water Quality Monitoring Technologies (3 papers) and Speech and Audio Processing (2 papers). The work is most often cited by research in Signal Processing (110 citations), Global and Planetary Change (164 citations) and Computer Vision and Pattern Recognition (104 citations). Muhammad Imran Ahmad has collaborated with scholars based in Malaysia, Iraq and United Kingdom. Frequent co-authors include C. D. Sinclair, Alan Werritty, Puteh Saad, Wai Lok Woo, Mohd Nazrin Md Isa, Satnam Dlay, Abdul Rahman Izaini Ghani, S.S. Dlay, Ruzelita Ngadiran and Rizalafande Che Ismail. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Hydrology.

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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