Publications
Interactive image and video classification using compressively sensed images
The paper investigates the use of compressively sensed images in interactive image classification. To speed-up the classification process and avoid costly reconstruction, we consider the use of a feed-forward neural network in a reduced complexity image domain. The interactive image and video classification systems have been used for real-time demonstrations that have been effectively utilized in outreach activities for attracting middle-school students to STEM.