The second workshop on wireless smart communication (2wsc'20)

About the Workshop :

After the success of the First Edition of 2WSC (2WSC'19), we are pleased to invite you to the Second Edition of 2WSC.

The Second Workshop on Wireless Smart Communication (2WSC'20) will be hosted by the Mohammadia School of Engineering (EMI), Mohammed V University in Rabat. This Workshop is organized by the Research Team in Smart Communication (ERSC) in collaboration with the Moroccan Association for Information and Communication Technologies Research and Applications (MAICTRA). 2WSC aims to:

• Gather up academic researchers in the area of Wireless Communication
• Present, discuss and confront recent research works
• Promote the exchange and cooperation between academic researchers
• Initiate Junior researchers to research tools (IoT, simulation tools, publication tools,...) through technical sessions.

Topics :

The 2WSC'20 will address current topics in the field of Wireless Communication. This current edition will focus on new technologies for smart wireless communication including, but is not limited to, the following topics:

• Internet of Things
• Networking and Communication
• IT Applications
• Embedded Systems and Software
• Intelligent Transportation System
• Artificial Intelligence
• Cloud Computing
• Data Analysis
• Wireless Sensor Network
• Big Data
• Crowd Sensing
• Network Data Analysis
• Wireless Network Security
• Cognitive Radio Network 

Workshops :

• IoT
• Latex
• NS3 

Speaker :

Aissam BERRAHOU received the M.Sc. degrees and Ph.D in computer science from the Mohammed V University, Mohammadia School Of Engineering, Rabat, Morocco in 2008 and 2015 respectively. He is now an assistant professor in National School of Computer Science And Systems Analysis, Mohammed V University. He is also member of the Review Panel of IEEE Transactions on Multimedia and Machine Vision and Applications (Springer). His research interest includes, embedded systems, optimization, deep learning, machine learning and computer vision.

Title: Deep learning for computer vision : concepts, architectures and applications
Abstract: Deep learning (DL) is a class of machine learning algorithms which enables computers to learn from examples. Deep learning techniques have been used successfully for variety of applications, including: automatic speech recognition, image recognition, natural language processing, drug discovery, and recommendation systems. In my talk I"ll present the fundamental concepts and different architectures of Deep Learning ; its applications and future directions for designing DL models for computer vision problems. Moreover, students will learn to implement, train, and validate their own neural network, and they will improve their understanding of the on-going research in computer vision field. 

Submission :

Authors are invited to submit papers related to the field of Smart Wireless Communication. Submitted papers must be written in English and should not exceed 8 pages in length, including all figures, tables, and references, using the IEEE template. All submissions will be reviewed on the basis of relevance, originality, importance and clarity. Extended version of papers including modifications will be submitted for publications to the Electronic Journal of Information Technology (revue-eTI). e-TI is indexed in bibliographical databases such as DOAJ and EBSCO and indexed in Google Scholar search engine. It is referenced by AUF, IMIST and ResearchGate.

Paper must be send in PDF format to: : عنوان البريد الإلكتروني هذا محمي من روبوتات السبام. يجب عليك تفعيل الجافاسكربت لرؤيته.

Venue :