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Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

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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

This book is included in DOAB.

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Keywords

  • actuation systems
  • adaptive classifier updating
  • ADAS
  • automated driving
  • automated-manual transition
  • Autonomous driving
  • autonomous driving assistance system
  • Autonomous Vehicle
  • autonomous vehicles
  • autopilot
  • biological vision
  • blind spot detection
  • camera
  • communications
  • convolutional neural network
  • convolutional neural network (CNN)
  • convolutional neural networks
  • cooperative systems
  • crash injury severity prediction
  • deep leaning
  • deep learning
  • depthwise separable convolution
  • discriminative correlation filter bank
  • driver monitoring
  • driverless
  • driving assistance
  • driving decision-making model
  • drowsiness detection
  • DSRC
  • dynamic path-planning algorithms
  • Electric vehicles
  • electrocardiogram (ECG)
  • emergency decisions
  • enhanced learning
  • ethical and legal factors
  • FPGA
  • fusion
  • Gabor convolution kernel
  • Gaussian kernel
  • generative adversarial nets
  • Geobroadcast
  • global region
  • GPU
  • image inpainting
  • infinity norm
  • Intelligent Transport Systems
  • interface
  • joystick
  • kernel based MIL algorithm
  • kinematic control
  • LiDAR
  • Machine learning
  • machine vision
  • maneuver algorithm
  • map generation
  • multi-sensor
  • n/a
  • Navigation
  • neural networks
  • object detection
  • object tracking
  • obstacle detection and classification
  • occlusion
  • optimization
  • p-norm
  • panoramic image dataset
  • parallel architectures
  • path planning
  • perception in challenging conditions
  • photoplethysmogram (PPG)
  • predictive
  • real-time object detection
  • recurrence plot (RP)
  • recurrent neural network
  • red light-running behaviors
  • relative speed
  • residual learning
  • road lane detection
  • road scene
  • smart band
  • squeeze-and-excitation
  • sub-region
  • support vector machine model
  • T-S fuzzy neural network
  • terrestrial vehicle
  • the emergency situations
  • total vehicle mass of the front vehicle
  • two-wheeled
  • urban object detector
  • VANET
  • vehicle dynamics
  • Vehicle-to-X communications
  • visual tracking

Links

DOI: 10.3390/books978-3-03921-376-4

Editions

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