visual attention networks

Visual attention networks are computer systems designed to mimic how humans focus on important parts of an image or scene. They analyze visual data and prioritize areas that are most relevant, enabling more efficient recognition and understanding. By selectively concentrating on key features, these networks improve tasks like image classification, object detection, and scene understanding. Essentially, they help machines "pay attention" to significant details within complex visual inputs, much like how humans glance at and process specific parts of their surroundings for better comprehension.