Ahmad Nickabadi
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications 3
- Metaheuristic Optimization Algorithms Research 3
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- Face recognition and analysis 4
- Video Analysis and Summarization 3
- Generative Adversarial Networks and Image Synthesis 2
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- Web Application Security Vulnerabilities 4
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- Advanced Malware Detection Techniques 3
- Speech and Audio Processing 2
- Co-authors
- Reza SafabakhshMohammad Mehdi EbadzadehAlexandre AlahiNavid Mohammadi FoumaniMorteza Haghir ChehreghaniMehdi GhateeMohammad Mehdi HomayounpourFarshad Almasganj
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsComputer Vision and Pattern Recognition
In The Last Decade
Ahmad Nickabadi
29 papers receiving 873 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 503
- Computational Theory and Mathematics 205
- Computer Vision and Pattern Recognition 191
- Control and Systems Engineering 162
- Industrial and Manufacturing Engineering 53
Countries citing papers authored by Ahmad Nickabadi
This map shows the geographic impact of Ahmad Nickabadi'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 Ahmad Nickabadi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmad Nickabadi more than expected).
Fields of papers citing papers by Ahmad Nickabadi
This network shows the impact of papers produced by Ahmad Nickabadi. 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 Ahmad Nickabadi. The network helps show where Ahmad Nickabadi may publish in the future.
Co-authorship network
The 21 scholars most cited alongside Ahmad Nickabadi, 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 | 2024 | 4 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 0 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 21 | |
| 9 | 2023 | 5 | |
| 10 | 2023 | 5 | |
| 11 | 2022 | 5 | |
| 12 | 2022 | 6 | |
| 13 | 2022 | 1 | |
| 14 | 2022 | 2 | |
| 15 | Threat of Adversarial Attacks on Face Recognition: A Comprehensive Survey. | 2020 | 5 |
| 16 | 2019 | 6 | |
| 17 | 2019 | 2 | |
| 18 | 2018 | 6 | |
| 19 | 2017 | 21 | |
| 20 | 2006 | 2 |
About Ahmad Nickabadi
Ahmad Nickabadi is a scholar working on Computer Vision and Pattern Recognition, Software and Signal Processing, having authored 31 papers that have together received 906 indexed citations. Recurring topics across this work include Face recognition and analysis (4 papers), Web Application Security Vulnerabilities (4 papers), Video Analysis and Summarization (3 papers), Anomaly Detection Techniques and Applications (3 papers), Metaheuristic Optimization Algorithms Research (3 papers), Advanced Malware Detection Techniques (3 papers), Speech and Audio Processing (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Artificial Intelligence (503 citations), Computational Theory and Mathematics (205 citations) and Computer Vision and Pattern Recognition (191 citations). Ahmad Nickabadi has collaborated with scholars based in Iran, Japan and Sweden. Frequent co-authors include Reza Safabakhsh, Mohammad Mehdi Ebadzadeh, Alexandre Alahi, Navid Mohammadi Foumani, Morteza Haghir Chehreghani, Mehdi Ghatee, Mohammad Mehdi Homayounpour, Farshad Almasganj, S. Mehdi Hashemi and Raghavendra Ramachandra. Their work appears in journals such as Expert Systems with Applications, Neurocomputing and Applied 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.