Mohsen Ali

728 citations
39 papers · 407 · h-index 14

Impact in

Papers in

Mohsen Ali

33 papers receiving 398 citations

Peers

Mohsen Ali
Comparison fields: 5 of 83
  • Computer Vision and Pattern Recognition 187
  • Computer Science Applications 47
  • Media Technology 63
  • Artificial Intelligence 126
  • Electronic, Optical and Magnetic Materials 50
Replace Tobias Franke with:
Tobias Franke Germany
Kai H. Chang United States
Hui Deng China
Chongyang Zhang China
Abhinandan Gangopadhyay United States
Matthias Schulz Germany
Heng Siong Lim Malaysia
Yuxi Wang China
Mehdi S. M. Sajjadi United States
Mohsen Ali relative to Tobias Franke Germany Tobias Franke's profile →
Citations per field
00.5×4.3×
Tobias Franke · 1×
Citations per year

Countries citing papers authored by Mohsen Ali

Since Specialization
Citations

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

Fields of papers citing papers by Mohsen Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201967
2 201334
3 202233
4
SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection
202130
5 202125
6 202025
7 202123
8 201916
9 202014
10 197914
11 201314
12 202214
13 202213
14 202113
15 202310
16 202310
17 20228
18 20197
19 20226
20 20226

About Mohsen Ali

Mohsen Ali is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Global and Planetary Change and Computational Mechanics, having authored 39 papers that have together received 407 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (11 papers), Advanced Image and Video Retrieval Techniques (6 papers), Domain Adaptation and Few-Shot Learning (5 papers), Remote-Sensing Image Classification (5 papers), Digital Imaging for Blood Diseases (4 papers), Anomaly Detection Techniques and Applications (4 papers), Flood Risk Assessment and Management (3 papers) and Metamaterials and Metasurfaces Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (187 citations), Computer Science Applications (47 citations), Media Technology (63 citations), Artificial Intelligence (126 citations) and Electronic, Optical and Magnetic Materials (50 citations). Mohsen Ali has collaborated with scholars based in Pakistan, United States and United Arab Emirates. Frequent co-authors include Waqas Sultani, Saeed‐Ul Hassan, Jeffrey Ho, Muhammad Qasim Mehmood, Muhammad Zubair, Francisco Herrera, Sebastián Ventura, Hajra Waheed, Naif Radi Aljohani and M. Saquib Sarfraz. Their work appears in journals such as IEEE Access, ISPRS Journal of Photogrammetry and Remote Sensing, Neurocomputing, Medical Image Analysis and Journal of Ambient Intelligence and Humanized Computing.

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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