Fares Fathy

Sensor Fusion and Perception for Autonomous Driving: A Critical Review of Modalities, AI Models, Algorithms, and Industry Configurations

A systematic analysis of the machine learning and deep learning models underpinning vehicle autonomy, spanning classical convolutional neural networks for object detection and semantic segmentation to recurrent and Transformer-based architectures for trajectory prediction and motion planning is presented.