ShuffleNet

When a neural network learns image labels, it may confuse a background item for the labeled object. New research avoids such mistakes.

Equipment that relies on computer vision while unplugged — mobile phones, drones, satellites, autonomous cars — need power-efficient models. A new architecture set a record for accuracy per computation.