Deep Manta performs multi-task deep learning

DeepManta, a flexible algorithm, can demonstrate visual object recognition for smart cities, such as identifying vehicles, their type and position and counting them. Different objects, such as miniature cars, move into a camera's field of view, where the AI will selectively recognize them. When a car is recognized, the algorithm generates a visual annotation, labeling the car with the logo of the brand and model information, and encompassing it with 2D and 3D boxes to locate it spatially in the video in real time. In addition to automotive applications, the algorithm's automated perception capacity opens up new services with significant social and business impacts. "DeepManta delivers one of the promises of AI: providing assistance to users by automatizing and parallelizing tasks that normally would require their full attention," says List's Stéphane David,"it excels at each individual task, but requires much less overall memory and processing power than parallel architectures that use one algorithm per task."