Design of parallel processing architectures for embedded deep learning techniques
@ Le2i laboratory (CNRS-Université Bourgogne Franche-Comté), France
In computer vision, object detection still represents one of the most challenging problems because it is prone to localization and classification error. State-of-the-art detectors are many based on a two-step process including region proposals followed by localization of objects in the candidate regions. Common region proposal techniques consumes significant running time to perform exhaustive search in the input image and outputs hundreds or thousands of potential regions of interest and metadata such as objectness score. This ESR project aims at developing a toolkit of real-time building blocks dedicated to intelligent computation of ROIs for object detection. SW for CPU/GPU platforms and HW for FPGA-based camera will be considered. Work will be done in collaboration with WP4-WP7 in which the building blocks can be reused in complex real-life applications.
Application deadline: Mar. 1, 2018