TinyML for Safe Driving: The Use of Embedded Machine Learning for Detecting Driver Distraction.
Thommas K. S. FloresMarianne SilvaMariana AzevedoThaís MedeirosMorsinaldo MedeirosIvanovitch SilvaMax Mauro Dias SantosDaniel G. CostaPublished in: MetroAutomotive (2023)
Keyphrases
- driving simulator
- machine learning
- driving behavior
- traffic safety
- traffic accidents
- driver assistance systems
- machine learning methods
- embedded systems
- artificial intelligence
- automatic detection
- car navigation
- road safety
- intelligent vehicles
- learning algorithm
- real time
- pattern recognition
- computer science
- computational intelligence
- machine learning algorithms
- semi supervised learning
- machine learning and data mining
- inductive learning
- learning tasks
- data mining
- computer vision
- decision trees
- data analysis
- supervised machine learning
- reinforcement learning
- support vector machine
- information extraction
- natural language processing
- digital images
- transfer learning
- knowledge discovery
- knowledge representation
- low cost
- dangerous situations
- learning problems
- text classification
- kernel methods