|Tagging images and videos on mobile devices is an open market. Many software companies recently began to work on deep learning techniques; however, such techniques are limited by the low-performance hardware of mobile phones. In addition, some of the existing products are task-specific and cannot be reprogramed to perform new tasks.
Researchers at Purdue University have developed a new system of hardware and software that can solve state-of-the-art, complex, vision tasks. This system includes a novel hardware architecture that provides low-power operation and simultaneously a high number of operations for a whole class of vision algorithms while maintaining complete programmability. This system adapts new tasks with minor reprogramming and scale more efficiently to new vision models.
-Can solve state-of-the-art, complex, vision tasks
-Provides low-power operation and simultaneously a high number of operations
-Adapt new tasks with minor reprogramming
-Scale more efficiently to new vision models
Dec 31, 2017
Dec 18, 2018
Mar 17, 2015
Jan 2, 2018
Mar 17, 2014
Purdue Office of Technology Commercialization
1801 Newman Road
West Lafayette, IN 47906
Phone: (765) 588-3475
Fax: (765) 463-3486