CAFFE (Convolutional Architecture for Fast Feature Embedding) is a deep learning framework, originally developed at UC Berkeley. It is open source, under a BSD license. It is written in C++, with a Python interface.
Type of optical sensor with lens and image signal processors, providing low-latency data feed to the dashboard and / or to further processing for computer vision tasks. Lens and ISP will vary depending on application, e.g. surround view cameras are likely to have a wider lens and thus capture more… read more
The construction zone assist system keeps the car within a narrower lane by way of steering corrections. To do this, the system takes data from video and ultrasonic sensors and calculates a safe distance on either side to vehicles in the next lane as well as to any crash barrier…. read more
Uses side-facing sensors such as RADAR, camera or ultrasonic sensors to alert the driver to traffic moving at a right-angle to the vehicle. Located near the front or rear of the vehicle, detecting traffic that comes from the side, especially in parking situations (to the rear) or blind corners (toward… read more