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Overview of recent advances of deep learning application in computer vision
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Journal of Computer Science & Systems Biology

ISSN: 0974-7230

Open Access

Overview of recent advances of deep learning application in computer vision


Joint Event on 5th World Machine Learning and Deep Learning Congress and World Congress on Computer Science, Machine Learning and Big Data

August 30-31, 2018 Dubai, UAE

Abed Benaichouche

Inception Institute of Artificial Intelligence, UAE

Scientific Tracks Abstracts: J Comput Sci Syst Biol

Abstract :

In recent years, deep learning (DL) has won numerous contests in computer vision and machine learning. In this presentation, we will present real world applications of Conventional Neuronal Network (CNN), Recurrent Network (RNN) and Generative Adversarial Network (GAN) in computer vision area. In the presentation, we will show a selection of recent research that Inception Institute of Artificial Intelligence (IIAI) is leading in the field of computer vision and artificial intelligence. For the CNN, we will present its application for face detection and annotation, demo for object detection and pose camera estimation. For the GANs, we will show its use for image colorization and art style transfer. And finally we present a new approach for face detection and super-resolution using both CNN and GAN models. For each demo we present the designed network, its limitations and the give perspectives for possible improvement.

Biography :

Abed Benaichouche has completed his PhD from Ecole Nationale Superieur des Mines de Paris and Postdoctoral studies from French Geological Survey. He is a Senior Research Engineer and Team Leader at Inception Institute of Artificial Intelligence, (IIAI) the UAE’s national research organization, which aims for breakthroughs in fundamental and applied AI research. He has published more than 10 papers in reputed journals and international conferences. Before joining IIAI, he has worked for 2 years in BRGM (France) as Research Engineer. He designed and developed the Suricate-Nat platform; interactive web platform to collect information and analyzing it using NLP techniques on natural disasters emitted by citizens using social networks Twitter. He was also the Project Manager of the development of international interoperable platform for multi-risk analysis.

E-mail: benaichouche.abed@ymail.com

abed.benaichouche@inceptioniai.org

 

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