Ali Mohammad‐Djafari

3.4k total citations
196 papers, 1.8k citations indexed

About

Ali Mohammad‐Djafari is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Ali Mohammad‐Djafari has authored 196 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 45 papers in Biomedical Engineering and 44 papers in Artificial Intelligence. Recurrent topics in Ali Mohammad‐Djafari's work include Medical Imaging Techniques and Applications (33 papers), Blind Source Separation Techniques (31 papers) and Sparse and Compressive Sensing Techniques (26 papers). Ali Mohammad‐Djafari is often cited by papers focused on Medical Imaging Techniques and Applications (33 papers), Blind Source Separation Techniques (31 papers) and Sparse and Compressive Sensing Techniques (26 papers). Ali Mohammad‐Djafari collaborates with scholars based in France, China and United States. Ali Mohammad‐Djafari's co-authors include Saïd Moussaoui, Jean‐François Bercher, Cédric Carteret, Hacheme Ayasso, Pierre Bessìère, Ning Chu, G. Demoment, David Brie, José Picheral and Hichem Snoussi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Cancer Research and Scientific Reports.

In The Last Decade

Ali Mohammad‐Djafari

175 papers receiving 1.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ali Mohammad‐Djafari France 24 358 327 323 309 231 196 1.8k
Jérôme Idier France 29 434 1.2× 656 2.0× 383 1.2× 540 1.7× 389 1.7× 144 3.2k
Yngve Selén Sweden 18 191 0.5× 107 0.3× 274 0.8× 629 2.0× 103 0.4× 38 2.4k
John J. Benedetto United States 23 149 0.4× 1.1k 3.3× 173 0.5× 531 1.7× 153 0.7× 122 2.7k
Xuejun Liao United States 21 420 1.2× 636 1.9× 781 2.4× 176 0.6× 142 0.6× 67 2.0k
Bo Zhang China 29 725 2.0× 981 3.0× 693 2.1× 99 0.3× 122 0.5× 229 3.4k
Haomin Zhou United States 22 144 0.4× 495 1.5× 144 0.4× 151 0.5× 81 0.4× 90 1.9k
S. Derin Babacan United States 18 524 1.5× 1.0k 3.2× 146 0.5× 330 1.1× 179 0.8× 56 2.2k
Clemens Elster Germany 31 831 2.3× 595 1.8× 115 0.4× 54 0.2× 142 0.6× 196 3.1k
Yuying Li China 17 234 0.7× 255 0.8× 119 0.4× 49 0.2× 111 0.5× 39 2.0k
B.R. Hunt United States 24 264 0.7× 1.4k 4.4× 196 0.6× 358 1.2× 139 0.6× 97 2.3k

Countries citing papers authored by Ali Mohammad‐Djafari

Since Specialization
Citations

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

Fields of papers citing papers by Ali Mohammad‐Djafari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Mohammad‐Djafari

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Mohammad‐Djafari. A scholar is included among the top collaborators of Ali Mohammad‐Djafari based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ali Mohammad‐Djafari. Ali Mohammad‐Djafari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Chu, Ning, et al.. (2025). Temperature calibration of surface emissivities with an improved thermal image enhancement network. Measurement. 257. 118325–118325. 1 indexed citations
3.
Chu, Ning, et al.. (2024). An Efficient Temperature Calibration Method Based on the Improved Infrared Forward Model and Bayesian Inference. IEEE Sensors Journal. 24(15). 24249–24262. 2 indexed citations
4.
Chu, Ning, et al.. (2024). A Separation-Based Localization Method Between Rotating and Static Sources. IEEE Signal Processing Letters. 31. 1359–1363. 1 indexed citations
5.
Sun, Zekun, et al.. (2024). An infrared-optical image registration method for industrial blower monitoring based on contour-shape descriptors. Measurement. 240. 115634–115634. 5 indexed citations
6.
Yu, Liang, et al.. (2023). 3D Non-Synchronous Measurements With Central Reference Based on Revolution and Autorotation of Spherical Microphone Array. IEEE Signal Processing Letters. 30. 518–522. 1 indexed citations
7.
Chu, Ning, et al.. (2023). High-Resolution Fast-Rotating Sound Localization Based on Modal Composition Beamforming and Bayesian Inversion. IEEE Signal Processing Letters. 30. 349–353. 4 indexed citations
8.
Li, Li, et al.. (2023). Abnormal Temperature Detection of Blower Components Based on Infrared Video Images Analysis. IEEE Sensors Journal. 24(2). 1919–1928. 2 indexed citations
9.
Makaremi, Masrour, et al.. (2023). An interpretable machine learning approach to study the relationship beetwen retrognathia and skull anatomy. Scientific Reports. 13(1). 18130–18130.
10.
Wang, Li, et al.. (2022). A Hierarchical Bayesian Fusion Method of Infrared and Visible Images for Temperature Monitoring of High-Speed Direct-Drive Blower. IEEE Sensors Journal. 22(19). 18815–18830. 4 indexed citations
11.
Li, Xiaomei, Ali Mohammad‐Djafari, Sandrine Dulong, et al.. (2013). A Circadian Clock Transcription Model for the Personalization of Cancer Chronotherapy. Cancer Research. 73(24). 7176–7188. 58 indexed citations
12.
Mohammad‐Djafari, Ali, Jean‐François Bercher, & Pierre Bessìère. (2011). BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: Proceedings of the 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. AIPC. 1305. 1 indexed citations
13.
Caticha, Ariel, Ali Mohammad‐Djafari, Jean‐François Bercher, & Pierre Bessìère. (2011). Entropic Inference. AIP conference proceedings. 20–29. 16 indexed citations
14.
Krylov, Vladimir A., Gabriele Moser, Sebastiano B. Serpico, et al.. (2011). Multichannel SAR Image Classification by Finite Mixtures, Copula Theory and Markov Random Fields. AIP conference proceedings. 319–326. 1 indexed citations
15.
You, Peng, et al.. (2011). Recognition-oriented Bayesian SAR imaging. IEEE Asia-Pacific Conference on Synthetic Aperture Radar. 1–4. 2 indexed citations
16.
Mohammad‐Djafari, Ali. (2010). Inverse Problems in Imaging and Computer Vision - From Regularization Theory to Bayesian Inference.. 5–7. 1 indexed citations
17.
Mohammad‐Djafari, Ali, et al.. (2006). Hierarchical Markovian models for 3D Computed Tomography in non destructive testing applications. European Signal Processing Conference. 1–5. 4 indexed citations
18.
Mohammad‐Djafari, Ali, et al.. (2006). Hierarchical markovian models for joint classification, segmentation and data reduction of hyperspectral images.. The European Symposium on Artificial Neural Networks. 359–364. 2 indexed citations
19.
Mohammad‐Djafari, Ali. (2001). Bayesian inference and maximum entropy methods in science and engineering : 20th international workshop, Gif-sur-Yvette, France 8-13 July 2000. American Institute of Physics eBooks. 1 indexed citations
20.
Mohammad‐Djafari, Ali, et al.. (1988). 3 - Utilisation de l'entropie dans les problèmes de restauration et de reconstruction d'images. Traitement du signal. 7 indexed citations

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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