New program picks out targets in a crowd quickly and efficiently

Phys. org  February 22, 2019
Previous work on visual search has focused on searching for perfect matches of a target after extensive category-specific training. An international team of researchers (Singapore, USA – University of Minnesota) shows that humans can efficiently and invariantly search for natural objects in complex scenes. They developed a biologically inspired computational model that can locate targets without exhaustive sampling and generalize to novel objects. They trained the model to look for something that had similar features to the example image of a dog. This enabled the model to generalize from a single dog image, to the “general concept of a dog”. The model could search images as fast as humans, even when searching for objects they’ve never seen before. The team is now programming their model with a better understanding of context…read more. Open Access TECHNICAL ARTICLE 

Credit: CC0 Public Domain