Please use this identifier to cite or link to this item:
http://dspace.ensta.edu.dz/jspui/handle/123456789/301| Title: | Comparative Analysis of Random Forest, YOLO, and Classical Lookup Table-based Approaches for Sign Language Classification |
| Authors: | Benbrahim, Tarek OUGERIRAH, Hamida (Directeur de thèse) |
| Keywords: | Lookup tables sign language Accuracy machine learning yolo Random Forest |
| Issue Date: | 2024 |
| Publisher: | ENSTA |
| Abstract: | A comparative analysis of three sign language classification methods: random forest, YOLO (You Look On{}ce), and look-up table method , the strengths and weaknesses of each method are examined diversity in terms of accuracy, speed, flexibility. |
| Description: | Mémoire de fin d’étude du Master: Systèmes Embarqués:Alger: Ecole Nationale Supérieure des Technologie Avancées(ex ENST): 2024 |
| URI: | http://dspace.ensta.edu.dz/jspui/handle/123456789/301 |
| Appears in Collections: | ART- Systèmes Embarqués |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| MFE_Benbrahim_SE - Département Génie Electrique et Informatique Industrielle.pdf | Mémoire du Master | 7.56 MB | Adobe PDF | View/Open |
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