COVID-19 X-rays Model Detection Using Convolution Neural Network.- Deep Learning Models Using Auxiliary Classifier GAN for Covid-19 Detection – a Comparative Study.- Feature Pyramid Network for COVID-19 Pneumonia Detection from Chest X-rays Images.- Explore the Relationship Between COVID-19 Testing Rates with the Number of Cases.- Deep Learning Method for Bone Abnormality Detection Using Multi-view X-rays.- A Deep Autoencoder based Multi-Criteria Recommender System.- Review on Supervised and Unsupervised Deep Learning Techniques for Hyperspectral Images Classification.- The Impact of COVID-19 on E-learning: Advantages and Challenges.- Commodity Image Retrieval Based on Convolutional Neural Network and Late Fusion.- Convolutional Neural Network for Fire Video Image Detection in the Thermal Power Plant.

This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco.  This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation,  AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications.     

Presents research in the field of Artificial Intelligence and Computer Vision Includes the outcomes of AICV 2021 held during June 28-30, 2021, in Settat, Morocco Serves as a reference resource for researchers and practitioners in academia and industry