Kamel Mekhnacha
- Automotive Engineering top 5%
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- Video Surveillance and Tracking Methods 6
- Building and Construction top 10%
- Artificial Intelligence top 10%
- Target Tracking and Data Fusion in Sensor Networks 9
- Bayesian Modeling and Causal Inference 3
- AI-based Problem Solving and Planning 3
- Gaussian Processes and Bayesian Inference 3
- Anomaly Detection Techniques and Applications 2
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- Robotics and Sensor-Based Localization 4
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- Statistical Methods and Bayesian Inference 1
Kamel Mekhnacha
17 papers receiving 362 citations
Peers
Comparison fields: 5 of 51
- Automotive Engineering 233
- Safety, Risk, Reliability and Quality 79
- Computer Vision and Pattern Recognition 120
- Building and Construction 71
- Artificial Intelligence 134
Countries citing papers authored by Kamel Mekhnacha
This map shows the geographic impact of Kamel Mekhnacha'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 Kamel Mekhnacha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kamel Mekhnacha more than expected).
Fields of papers citing papers by Kamel Mekhnacha
This network shows the impact of papers produced by Kamel Mekhnacha. 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 Kamel Mekhnacha. The network helps show where Kamel Mekhnacha may publish in the future.
Co-authorship network
The 15 scholars most cited alongside Kamel Mekhnacha, 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 | 2013 | 39 | |
| 2 | 2011 | 214 | |
| 3 | 2010 | 2 | |
| 4 | 2009 | 4 | |
| 5 | Bayesian Occupancy Filter based "Fast Clustering-Tracking" algorithm | 2008 | 16 |
| 6 | Robust multi-target sensing/tracking in the Bayesian Occupancy Filter framework | 2008 | 1 |
| 7 | 2008 | 25 | |
| 8 | 2008 | 7 | |
| 9 | 2007 | 9 | |
| 10 | An Efficient Formulation of the Bayesian Occupation Filter for Target Tracking in Dynamic Environments | 2006 | 1 |
| 11 | Velocity Estimation on the Bayesian Occupancy Filter for Multi-Target Tracking | 2006 | 2 |
| 12 | A unifying framework for exact and approximate Bayesian inference | 2006 | 1 |
| 13 | 2006 | 46 | |
| 14 | 2001 | 1 | |
| 15 | 2001 | 11 | |
| 16 | 1998 | 3 | |
| 17 | 1998 | 1 |
About Kamel Mekhnacha
Kamel Mekhnacha is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 17 papers that have together received 383 indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (9 papers), Video Surveillance and Tracking Methods (6 papers), Robotics and Sensor-Based Localization (4 papers), Bayesian Modeling and Causal Inference (3 papers), AI-based Problem Solving and Planning (3 papers), Gaussian Processes and Bayesian Inference (3 papers), Anomaly Detection Techniques and Applications (2 papers) and Statistical Methods and Bayesian Inference (1 paper). The work is most often cited by research in Automotive Engineering (233 citations), Safety, Risk, Reliability and Quality (79 citations) and Computer Vision and Pattern Recognition (120 citations). Kamel Mekhnacha has collaborated with scholars based in France, Germany and United States. Frequent co-authors include Christian Laugier, Christopher Tay, Yong Mao, Mathias Perrollaz, John-David Yoder, Amaury Nègre, I.E. Paromtchik, Pierre Bessìère, Emmanuel Mazer and Manuel Yguel.
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.