Category: News

Abstract: Generative adversarial networks (GANs) have shown tremendous promise in learning to generate data and effective at aiding semi-supervised classification. However, to this point, semi-supervised GAN methods make the assumption that the unlabeled data set contains only samples of the joint distribution of the classes of interest, referred to as inliers. Consequently, when presented with […]

Congratulations to our labmates: Joshua Peeples, Connor McCurley, Sarah Walker,  Dylan Stewart and Alina Zare! Their paper, “LEARNABLE ADAPTIVE COSINE ESTIMATOR (LACE) FOR IMAGE CLASSIFICATION “, was recently accepted to IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2022. In the paper, the authors propose a new loss to improve feature discriminability and classification […]

Abstract: In this work, we propose a new loss to improve feature discriminability and classification performance. Motivated by the adaptive cosine/coherence estimator [42] (ACE), our proposed method incorporates angular information that is inherently learned by artificial neural networks. Our learnable ACE (LACE) transforms the data into a new “whitened” space that improves the inter-class separability […]

Abstract: Purpose: Root system architectures are complex, multidimensional, and challenging to characterize effectively for agronomic and ecological discovery. Methods: We propose a new method, Spatial and Texture Analysis of Root System architecture with Earth mover’s Distance (STARSEED), for comparing root architectures that incorporate spatial information through a novel application of the Earth Mover’s Distance (EMD). […]

We are pleased to welcome Brian Hicks as one of our new undergraduate research assistants in 2021! Brian majors in Computer Science in the UF Department of Computer & Information Science & Engineering. Brian works on segmentation of Blueberry root images. The goal is to apply a model pre-trained on Peanut root images to Blueberry […]

We are pleased to welcome Matthew Schrank as one of our new undergraduate research assistants in 2021! Matthew majors in Computer Science in the UF Department of Computer & Information Science & Engineering. He joins us the UF team of 9-university project that aims at developing switchgrass strains, which can be converted to biofuel while […]

Congratulations to our labmates and collaborators: Tierui Zou, Nader Aljohani, Keerthiraj Nagaraj, Sheng Zou, Cody Ruben, Arturo Bretas, Alina Zare and Janise McNair! Their paper, “A Network Parameter Database False Data Injection Correction Physics-Based Model: A Machine Learning Synthetic Measurement-Based Approach “, was recently accepted to Applied Sciences. In the paper, the authors present an […]

We are excited to welcome Darren Koenenn as a new Ph.D. student to The Machine Learning and Sensing Lab! Darren earned his B.S. in Computer Science at the University of South Alabama in 2016. Darren is a *SMART scholar in collaboration with U.S. Naval Surface Warfare Center Panama City Division. He plans on researching topic […]

The Machine Learning and Sensing Lab is excited to welcome Timothy Lu as one of our new PhD students in Fall 2021! Tim has recently earned his B.S. in Computer Engineering at the University of Wisconsin-Stout. He is starting to work on data reconstruction powered by Machine Learning. This is a subject Tim would like […]

  The Machine Learning and Sensing Lab is excited to welcome Meilun Zhou as a new Ph.D. student! Meilun received a SMART (Science, Mathematics, and Research for Transformation) Scholarship from the Department of Defense, which funds his PhD research. He received his BS degree in Computer Engineering from the Mississippi State University, Starkville, MS in […]