@conference {39533,
	title = {A Comparative Study of State-of-the-Art methods for vision-based Obstacle Detection},
	booktitle = {International Conference on Advances in Communication Technology,Computing and Engineering  (ICACTCE) - 2021},
	year = {Forthcoming},
	month = {24 March 2021},
	abstract = {Research into vision-based obstacle detection systems plays a fundamental role in developing autonomous vehicles and intelligent transportation systems. In fact, an intelligent vehicle should be ready to discover vehicles and possible obstacles along its route. This paper presents a comparative study of existing state-of-the-art methods for obstacle detection. However, there have been a large number of studies that thoroughly explored various types of state-of-the-art methods for obstacle detection. Here, this paper compares three methods in obstacle detection, namely the {\textquotedblleft}Robust obstacle detection for ADAS using distortions of IPM of a monocular camera{\textquotedblright}, {\textquotedblleft}Robust Obstacle Detection and Recognition for DAS{\textquotedblright}, and {\textquotedblleft}Real-time Obstacle Detection Over Rails Using Deep CNN{\textquotedblright} and analyzes the obtained results.\&nbsp;},
	author = {Abderaouf Menacer and Larbi GUEZOULI and Lyamine Guezouli}
}
