Comparative Analysis of Random Forest, YOLO, and Classical Lookup Table-based Approaches for Sign Language Classification

Please use this identifier to cite or link to this item: http://dspace.ensta.edu.dz/jspui/handle/123456789/301

Full metadata record

DC Field	Value	Language
dc.contributor.author	Benbrahim, Tarek	-
dc.contributor.author	OUGERIRAH, Hamida (Directeur de thèse)	-
dc.date.accessioned	2025-03-11T08:31:02Z	-
dc.date.available	2025-03-11T08:31:02Z	-
dc.date.issued	2024	-
dc.identifier.uri	http://dspace.ensta.edu.dz/jspui/handle/123456789/301	-
dc.description	Mémoire de fin d’étude du Master: Systèmes Embarqués:Alger: Ecole Nationale Supérieure des Technologie Avancées(ex ENST): 2024	en_US
dc.description.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.	en_US
dc.language.iso	en	en_US
dc.publisher	ENSTA	en_US
dc.subject	Lookup tables	en_US
dc.subject	sign language	en_US
dc.subject	Accuracy	en_US
dc.subject	machine learning	en_US
dc.subject	yolo	en_US
dc.subject	Random Forest	en_US
dc.title	Comparative Analysis of Random Forest, YOLO, and Classical Lookup Table-based Approaches for Sign Language Classification	en_US
dc.type	Article	en_US
Appears in Collections:	ART- Systèmes Embarqués

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