cREAtIve: reconfigurable embedded artificial intelligence

Poona Bahrebar, Leon Denis, Maxim Bonnaerens, Kristof Coddens, J. Dambre, W. Favoreel, I. Khvastunov, A. Munteanu, Hung Nguyen-Duc, S. Schulte, D. Stroobandt, Ramses Valvekens, N. V. D. Broeck, Geert Verbruggen
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引用次数: 0

Abstract

cREAtIve 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.
创造性:可重构的嵌入式人工智能
cREAtIve的目标是为汽车和交通监控应用开发新颖的高适应性嵌入式深度学习解决方案,包括位置传感器处理,基于激光雷达的场景解释,以及交通摄像头系统热图像中的物体检测和分类。这些应用都需要深度学习解决方案,这些解决方案适合在资源有限的嵌入式设备上部署,并具有对不断变化的环境条件的高适应性和鲁棒性。cREAtIve开发知识、工具和方法,使硬件高效、适应性强、强大的深度学习成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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