dc.contributor.author |
Chettouh, Jugurtha |
|
dc.contributor.author |
Abbaci, Aissa |
|
dc.contributor.author |
Mezzah, Samia ; promotrice |
|
dc.date.accessioned |
2022-01-06T10:02:49Z |
|
dc.date.available |
2022-01-06T10:02:49Z |
|
dc.date.issued |
2021 |
|
dc.identifier.uri |
http://hdl.handle.net/123456789/17718 |
|
dc.description |
Option : Réseaux et Télécommunications |
en_US |
dc.description.abstract |
The dissertation is organized as follows. Chapter I present an overview of intelligent video surveillance systems in IoT environment. In chapter II, we recall principles of machine learning, Deep Learning and Computer Vision. Chapter III gives the architecture of the proposed intelligent embedded vision system with the description of the main hardware and software aspect. In chapter IV, we describe the software implementation of the proposed system for the generation of the video summary. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Université Abderahmene Mira .Bejaia |
en_US |
dc.subject |
Intelligent embedded vision : Deep learning and computer vision : IOT |
en_US |
dc.title |
Intelligent embedded vision for summarization of multi-view videos in IOT. |
en_US |
dc.type |
Thesis |
en_US |