Farid Boussaïd
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- Advanced Image and Video Retrieval Techniques 15
- Advanced Neural Network Applications 14
- Face recognition and analysis 12
- Bioengineering top 2%
- Analytical Chemistry and Sensors 14
- Media Technology top 1%
- Image Processing Techniques and Applications 11
- Human-Computer Interaction top 2%
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- CCD and CMOS Imaging Sensors 25
- Gas Sensing Nanomaterials and Sensors 12
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- Advanced Chemical Sensor Technologies 15
Farid Boussaïd
136 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Computer Vision and Pattern Recognition 1.5k
- Bioengineering 173
- Media Technology 258
- Human-Computer Interaction 133
- Nuclear Energy and Engineering 11
Countries citing papers authored by Farid Boussaïd
This map shows the geographic impact of Farid Boussaïd'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 Farid Boussaïd with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Farid Boussaïd more than expected).
Fields of papers citing papers by Farid Boussaïd
This network shows the impact of papers produced by Farid Boussaïd. 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 Farid Boussaïd. The network helps show where Farid Boussaïd may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Farid Boussaïd, 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 | 2025 | 0 | |
| 2 | 2025 | 12 | |
| 3 | 2025 | 4 | |
| 4 | 2025 | 0 | |
| 5 | 2025 | 0 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 13 | |
| 8 | 2024 | 0 | |
| 9 | 2023 | 22 | |
| 10 | 2023 | 8 | |
| 11 | 2023 | 24 | |
| 12 | 2023 | 0 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 5 | |
| 15 | 2022 | 49 | |
| 16 | Spatial, Structural and Temporal Feature Learning for Human Interaction Prediction. | 2016 | 7 |
| 17 | How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances | 2015 | 6 |
| 18 | 2011 | 57 | |
| 19 | A CMOS imager with on-chip processing for image enhancement and edge detection | 2001 | 4 |
| 20 | 2000 | 5 |
About Farid Boussaïd
Farid Boussaïd is a scholar working on Computer Vision and Pattern Recognition, Bioengineering and Media Technology, having authored 151 papers that have together received 3.4k indexed citations. Recurring topics across this work include CCD and CMOS Imaging Sensors (25 papers), Advanced Chemical Sensor Technologies (15 papers), Advanced Image and Video Retrieval Techniques (15 papers), Analytical Chemistry and Sensors (14 papers), Advanced Neural Network Applications (14 papers), Face recognition and analysis (12 papers), Gas Sensing Nanomaterials and Sensors (12 papers) and Image Processing Techniques and Applications (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Bioengineering (173 citations) and Media Technology (258 citations). Farid Boussaïd has collaborated with scholars based in Australia, Hong Kong and China. Frequent co-authors include Mohammed Bennamoun, Amine Bermak, Ferdous Sohel, Laurent Valentin Jospin, Senjian An, Hamid Laga, Wray Buntine, Lian Xu, Qiuhong Ke and Xiaojin Zhao. Their work appears in journals such as Pattern Recognition, Australasian Journal of Paramedicine, IEEE Transactions on Image Processing, Neurocomputing and IEEE Access.
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.