This book presents the proceedings of the 3rd International Conference on Artificial Intelligence and Computer Vision (AICV’2023) which will be held in Marrakesh, Morocco, during March 05–07, 2023. This international conference, which highlighted essential research and developments in the fields of artificial intelligence and computer visions, was organized by the computer, Networks, Mobility and Modeling Laboratory (IR2M), Faculty of Sciences and Techniques, Hassan First University, Settat, Morocco, the Scientific Research Group in Egypt (SRGE), Cairo University, and the Automated Systems & Soft Computing Lab (ASSCL), Prince Sultan University, Riyadh, Saudi Arabia. The book is divided into sections, covering the following topics: swarm-based optimization mining and data analysis, deep learning and applications, machine learning and applications, image processing and computer vision, sentiment analysis, and recommendation systems, and software-defined network and telecommunication.
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Convolutional Sparse Autoencoder for Emotion Recognition.- Lung Cancer Classification Model Using Convolution Neural Network.- An Enhanced Deep learning Approach for Breast Cancer Detection In Histopathology Images.- Reducing Deep Learning Complexity Toward a Fast and Efficient Classification of Traffic Signs.- Reducing Deep Learning Complexity Toward a Fast and Efficient Classification of Traffic Signs.- Skin Cancer Detection Based on Deep Learning Methods.- Predicted Phase Using Deep Neural Networks to Enhance Esophageal Speech.- State of the Art Literature on Anti-Money Laundering using Machine Learning and Deep Learning Techniques.- The Reality of Artificial Intelligence Skills Among Eighth-Grade Students in Public Schools.- A Deep Neural Network Architecture for Extracting Contextual Information.- Feedforward Neural Network in Cancer Treatment Response Prediction.- A Genetic Algorithm Approach Applied to the Cover set Scheduling Problem for Maximizing Wireless Sensor Networks Lifetime.- Application of Machine Learning to Sentiment Analysis.- Robust Vehicle Detection by Using Deep Learning Feature and Support Vector Machine.
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