Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)John Ball , Bo Tang This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR and camera processing, ethics, and communications. Several new datasets are also provided for future research work. Researchers and others interested in these topics will find important advances contained in this book. |
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accuracy achieve algorithm analysis application automated autonomous beacon block calculate camera changes classifier communications compared complex Computer Vision Conference on Computer considered convolution correlation corresponding crash CrossRef dataset decision deep developed discriminative distance driving effect emergency environment Equation estimation evaluation experiments extraction Faster Figure filter Finally frame function IEEE implementation improved increases indicates injury severity input International lane layer learning LiDAR measures method module multiple neural network object detection obtained operations optimization output parameters Pattern performance points position prediction presented problem Proceedings proposed range real-time Recognition reduce reference region represents respectively road robot samples scale scene score selected sensor shows signals signs simulation situations speed Table task threshold tracker tracking traffic types urban variables vehicle