New Innovations In Image Segmentation For Edge devices

Image segmentation used to require large, compute-intensive neural networks.  Running deep learning models without connecting to cloud or GPU servers was a huge challenge. Now, researchers at DarwinAI and the University of Waterloo have designed a new neural network architecture called ‘AttendSeg,’ that can perform image segmentation on edge or low computational devices.  Image segmentation has a vital role to play in computer vision advancements. The goal of segmentation is to simplify or change the representation of an image into something more meaningful and easier to analyse. The use cases include self-driving vehicles, video surveillance, traffic control systems, etc. In a paper titled ‘AttendSeg: A Tiny Attention Condenser Neural Network for Semantic Segmentatio