Bahrebar, PoonaPoonaBahrebarDenis, LeonLeonDenisBonnaerens, MaximMaximBonnaerensCoddens, KristofKristofCoddensDambre, JoniJoniDambreFavoreel, WouterWouterFavoreelKhvastunov, IlliaIlliaKhvastunovMunteanu, AdrianAdrianMunteanuHung Nguyen-DucSchulte, StefanStefanSchulteStroobandt, DirkDirkStroobandtValvekens, RamsesRamsesValvekensVan den Broeck, NickNickVan den BroeckVerbruggen, GeertGeertVerbruggen2023-06-222023-06-202023-06-202023-06-2220219781450384049/WOS:000934880500030https://imec-publications.be/handle/20.500.12860/42064cREAtIve targets the development of novel highly-adaptable embedded deep learning solutions for automotive and traffic monitoring applications, including position sensor processing, scene interpretation based on LiDAR, and object detection and classification in thermal images for traffic camera systems. These applications share the need for deep learning solutions tailored for deployment on embedded devices with limited resources and featuring high adaptability and robustness to changing environmental conditions. cREAtIve develops knowledge, tools and methods that enable hardware-efficient, adaptable, and robust deep learning.Proceedings paper10.1145/3457388.3458857978-1-4503-8404-9WOS:000934880500030