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Wissam Kaddah
9
Documents
Identifiants chercheurs
- wkaddah
- 0000-0001-9014-3053
- Google Scholar : https://scholar.google.fr/citations?user=GGmDRRcAAAAJ&hl=en&oi=ao
- IdRef : 253136423
Présentation
**Wissam Kaddah** graduated from the engineering school “ISEN Yncréa Ouest” in Brest, France, in October 2014. From November 2014 to September 2015, he joined the ACTRIS Company in Brest, France, and worked with the L@bISEN Laboratory, on a major European project for the inventory of road assets. Then, he started his Ph.D. in signal and image processing with a dissertation about automatic pavement crack detection on images, which was supported by ACTRIS. He received the Ph.D. degree from the University of Western Brittany in Brest, France, in December 2018. Since the beginning of 2019, he has joined the ISEN Yncréa Ouest as a lecturer-researcher. His research interest includes signal and image processing: pattern detection and recognition (faces, shapes, road signs, etc.) — segmentation of thin structures on the road (cracks, etc.) — connected space (behavioral study, analysis of social and educational interactions, etc.) using artificial intelligence. He has authored/co-authored around 20 research publications in peer-reviewed reputed journals and conferences proceedings on a wide variety of theoretical and experimental topics (<https://linktr.ee/wkaddah>).
Associate Professor at ISEN Yncréa Ouest - [L@bISEN](https://isen-brest.fr/labisen/ "L@bISEN") - [LSL Team](https://isen-brest.fr/labisen/structure-labisen/lsl-light-scatter-learning/ "LSL Team")
Signal processing - Image Processing - Artificial Intelligence (AI) - Decision
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Behavioral Analysis and Individual Tracking Based on Kalman Filter: Application in an Urban EnvironmentSensors, 2021, 21 (21), pp.7234. ⟨10.3390/s21217234⟩
Article dans une revue
hal-03411220v1
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Automatic darkest filament detection (ADFD): a new algorithm for crack extraction on two-dimensional pavement imagesThe Visual Computer, 2020, 36 (7), pp.1369-1384. ⟨10.1007/s00371-019-01742-2⟩
Article dans une revue
hal-03045714v1
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Optimized minimal path selection (OMPS) method for automatic and unsupervised crack segmentation within two-dimensional pavement imagesThe Visual Computer, 2019, 35 (9), pp.1293-1309. ⟨10.1007/s00371-018-1515-9⟩
Article dans une revue
hal-03038641v1
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