The Machine Learning and Sensing Lab is excited to welcome Satya Krishna Pothapragada as a new Ph.D. student! Satya Krishna is a PhD student from India who is interested in applying Artificial Intelligence and Machine Learning Techniques to solve… Read More
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Welcome new PhD student Spencer Chang!
The Machine Learning and Sensing Lab is excited to welcome Spencer Chang as a new Ph.D. student in our group! Spencer Chang is from California and interested in practically all things related to machine and deep learning. He received… Read More
Welcome new PhD student Matt Wein!
The Machine Learning and Sensing Lab is excited to welcome Matt Wein as a new PhD student! Matt will be analyzing hyperspectral imagery for macrosystems under the Integrating Data science with Trees and Remote Sensing (IDTReeS) project. Matt’s research… Read More
Welcome new PhD student Anna Hampton!
The Machine Learning and Sensing Lab is excited to welcome Anna Hampton as a new Ph.D. student! Anna is a first year PhD student. She received her undergraduate degrees in mathematics and statistics from the University of Florida. Her… Read More
Welcome new PhD student Atayliya Irving!
The Machine Learning and Sensing Lab is excited to welcome Atayliya Irving a first year Ph.d. student interested in machine learning and artificial intelligence with a focus on human interactions! Atayliya received her B.S. degree in computer science from… Read More
Congratulations to Dr. Connor McCurley, our lab’s latest PhD graduate!
It is a great pleasure and honor for everyone in Gatorsense that one of our labmates has achieved his goal. Congratulations to Dr. Connor McCurley for graduating with his Ph.D.! Connor’s dissertation is titled “Discriminative Feature Learning with Imprecise, Uncertain, and… Read More
Bag-level classification network for infrared target detection accepted to SPIE, 2022!
Congratulations to our labmates and collaborators: Connor H. McCurley, Daniel Rodriguez, Chandler Trousdale, Arielle Stevens, Anthony Baldino, Eugene Li, Isabella Perlmutter, and Alina Zare. Their paper, “Bag-level classification network for infrared target detection”, was recently accepted to Proc. SPIE 12096, Automatic… Read More
Addressing the Inevitable Imprecision: Multiple Instance Learning for Hyperspectral Image Analysis
Abstract: In many remote sensing and hyperspectral image analysis applications, precise ground truth information is unavailable or impossible to obtain. Imprecision in ground truth often results from highly mixed or sub-pixel spectral responses over classes of interest, a mismatch between the precision… Read More
Welcome New Undergraduate Research Assistant Kaniel Vicencio!
The Machine Learning and Sensing Lab is excited to welcome our newest lab member, Kaniel Vicencio! Kaniel is a second-year pursuing his undergrad degree in computer science. In his free time, he likes to go climbing. He’s interested in machine… Read More
Bag-level Classification Network for Infrared Target Detection
Abstract: Aided target detection in infrared data has proven an important area of investigation for both military and civilian applications. While target detection at the object or pixel-level has been explored extensively, existing approaches require precisely-annotated data which is often… Read More