Adel Ammar

2.5k citations
68 papers · 1.8k · 2 hit papers · h-index 24

Impact in

Papers in

Adel Ammar

65 papers receiving 1.7k citations

Adel Ammar's Hit Papers

Gnss-denied unmanned aerial vehicle navigation: analyzing computational complexity, sensor fusion, and localization methodologies 2025 · 28 citations
280+1+3Years since publication50100150200

Peers

Adel Ammar
Comparison fields: 5 of 127
  • Computer Vision and Pattern Recognition 793
  • Health Informatics 27
  • Neurology 123
  • Aerospace Engineering 387
  • Artificial Intelligence 416
Replace Akif Durdu with:
Akif Durdu Türkiye
Doaa Sami Khafaga Saudi Arabia
Mohana India
Faliang Chang China
Lin Meng Japan
Jeongmin Park South Korea
Ahmed Abdelgawad United States
Bo Ma China
Ying Cai China
Lei Qi China
Adel Ammar relative to Akif Durdu Türkiye Akif Durdu's profile →
Citations per field
00.5×2×4×6×8.5×
Akif Durdu · 1×
Citations per year

Countries citing papers authored by Adel Ammar

Since Specialization
Citations

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

Fields of papers citing papers by Adel Ammar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Drone Deep Reinforcement Learning: A Review
Hit paper breakdown →
2021222
2 2022143
3 2017137
4 2015115
5 201476
6 201773
7 202166
8 202060
9 201350
10 202350
11 202149
12 201448
13 202146
14 201841
15 202238
16 202036
17 202135
18 202334
19 201429
20 201529

About Adel Ammar

Adel Ammar is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence, Aerospace Engineering and Signal Processing, having authored 68 papers that have together received 1.8k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (18 papers), Advanced Neural Network Applications (11 papers), Robotics and Sensor-Based Localization (11 papers), Optimization and Search Problems (8 papers), Anomaly Detection Techniques and Applications (6 papers), Video Surveillance and Tracking Methods (6 papers), Network Security and Intrusion Detection (6 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (793 citations), Health Informatics (27 citations), Neurology (123 citations), Aerospace Engineering (387 citations) and Artificial Intelligence (416 citations). Adel Ammar has collaborated with scholars based in Saudi Arabia, Tunisia and Portugal. Frequent co-authors include Anis Koubâa, Bilel Benjdira, Hachémi Bennaceur, Imen Chaari, Maram Alajlan, Wadii Boulila, Ahmad Taher Azar, Tarek Abbes, Azza Allouch and Sahar Trigui. Their work appears in journals such as Electronics, Applied Sciences, Remote Sensing, Sensors and Soft 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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