DC Field | Value | Language |
dc.contributor.author | HARIR, MOhammed EL-Amine | - |
dc.contributor.author | HARRIR, HAbib Abdelghani | - |
dc.date.accessioned | 2022-11-08T09:08:59Z | - |
dc.date.available | 2022-11-08T09:08:59Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | https://repository.esi-sba.dz/jspui/handle/123456789/312 | - |
dc.description | Supervisor : Mr Mohamed ELARBI BOUDIHIR
Mr Mohammed Yassine KAZI TANI | en_US |
dc.description.abstract | Computer Vision, Also called machine vision is a multidisciplinary domain that could be
called a sub domain of artificial intelligence (AI) and machine learning (ML), it uses some
specialized methods and makes use of algorithms. The main objective of computer vision is to
understand and recognize the content of digital images. Usually this involves developing
methods and functions that aim to reproduce the capability of humans.
Computer Vision is defined as a domain of study that seeks to develop mechanisms to
aid computers "see" and understand the content of digital images and video, it is nothing but a
scientific domain that allows computers to capture, interpret, understand, and process the
objects that are visually perceivable. With the help of AI and deep learning models, machine
vision systems are capable of understanding the captured digital images and react suitably.
Object Detection has been widely used in a lot of fields such as face detection, detecting
vehicles and walkers on streets, and autonomous vehicles. It not only covers classifying
objects and recognizing them in an image, but also localizes those objects and draws bounding
boxes around them. That’s why most of the successful object detection networks make use of
neural network based image classifiers in conjunction with object detection techniques.
Tensorflow Object Detection API is an open source framework based on Google’s TensorFlow
which lets us create, train and deploy object detection models | en_US |
dc.language.iso | en | en_US |
dc.title | Real time Object detection for visually impaired | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Master
|