Mohib Ullah

2.2k citations
105 papers · 1.2k · h-index 19

Impact in

Papers in

Mohib Ullah

88 papers receiving 1.2k citations

Peers

Mohib Ullah
Comparison fields: 5 of 121
  • Computer Vision and Pattern Recognition 566
  • Artificial Intelligence 415
  • Signal Processing 107
  • Experimental and Cognitive Psychology 129
  • Human-Computer Interaction 53
Replace Habib Ullah with:
Habib Ullah Pakistan
Manuel Domínguez-Morales Spain
Abdelmalik Taleb‐Ahmed France
Mohammed Zakariah Saudi Arabia
Jia Guo China
Wasiq Khan United Kingdom
AbdulMalik S. Al‐Salman Saudi Arabia
Enver Sangineto Italy
Alfredo Milani Italy
Alexander Agung Santoso Gunawan Indonesia
Mohib Ullah relative to Habib Ullah Pakistan Habib Ullah's profile →
Citations per field
00.5×1.5×2.0×
Habib Ullah · 1×
Citations per year

Countries citing papers authored by Mohib Ullah

Since Specialization
Citations

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

Fields of papers citing papers by Mohib Ullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohib Ullah, 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 Mohib Ullah Line = papers co-authored together Mohib Ullah links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201991
2 202184
3 201979
4 202367
5 202257
6 202254
7 202049
8 201847
9 202136
10 202034
11 201833
12 201832
13 201831
14 201927
15 201625
16 201725
17 201824
18 202418
19 202318
20 201718

About Mohib Ullah

Mohib Ullah is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Computer Networks and Communications and Molecular Biology, having authored 105 papers that have together received 1.2k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (22 papers), Human Pose and Action Recognition (14 papers), Anomaly Detection Techniques and Applications (14 papers), Advanced Image and Video Retrieval Techniques (7 papers), Remote-Sensing Image Classification (6 papers), Animal Behavior and Welfare Studies (6 papers), COVID-19 diagnosis using AI (5 papers) and Remote Sensing and Land Use (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (566 citations), Artificial Intelligence (415 citations), Signal Processing (107 citations), Experimental and Cognitive Psychology (129 citations) and Human-Computer Interaction (53 citations). Mohib Ullah has collaborated with scholars based in Norway, Pakistan and Saudi Arabia. Frequent co-authors include Faouzi Alaya Cheikh, Habib Ullah, Sultan Daud Khan, Muhammad Uzair, Muhammad Mudassar Yamin, Basel Katt, Abdulrahman Alreshidi, Muhammad Sajjad, Ahmed Mohammed and Khan Muhammad. Their work appears in journals such as IEEE Access, Alexandria Engineering Journal, Wireless Personal Communications, Neurocomputing and Biomedical Signal Processing and Control.

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.

Explore authors with similar magnitude of impact