Multi-task deep learning algorithm speeds up in-video analytics

The result of more than 10 years of research at List, the flexible algorithm dubbed DeepManta combines a native multi-task architecture with enhancements to conventional deep-learning algorithms, allowing the AI system to extract different types and levels of information simultaneously and in real-time. To be demonstrated at CES 2018, DeepManta is able to selectively recognize and extract objects from a video stream, for example to identify vehicles, their type and position and counting them. At CES, global supplier of advanced automotive technology Valeo will partner with List to demonstrate DeepManta's support for autonomous driving. The demonstration setup includes a video stream captured by a stationary camera and displayed live on a screen. Different objects, such as miniature cars, move into the camera's field of view, where the AI algorithm selectively recognizes them, automatically generating visual annotations, labelling the cars with the logo of their make together with model information.