The Machine Learning and Sensing Laboratory develops machine learning methods for autonomously analyzing and understanding sensor data. We investigate and develop artificial intelligence, machine learning, pattern recognition, computational intelligence, signal processing, and information fusion methods for application to sensing. Applications we have studied include landmine and explosive object detection, automated plant phenotyping, sub-pixel target detection, and underwater scene understanding. We have developed algorithms for ground-penetrating radar, hyperspectral imagery, electromagnetic induction data, synthetic aperture SONAR, and minirhizotron imagery.