Vision and Learning Group

West Virginia University
We investigate new and fundamental problems and applications in computer vision and machine learning research. We develop novel techniques for endowing machines with high-level visual processing capabilities, much like humans use their visual system for action. We do so by deriving new machine learning and computational tools that account for the physics, semantics, and dynamics of the visual world. The outcome of this research is applicable to areas such as image and video analysis and reasoning, medical and biomedical imaging and data science applications, biometrics, autonomous navigation, robotics, and many others.

Woodburn Hall Deep Styled

Research Highlights

Out-of-Distribution Learning

Out-of-Distribution Learning

Out-of-Distribution learning is concerned with developing methods where the distribution of the data processed at test time may be different from the distribution of the data used during the training of a model.

Immersive Analytics

Immersive Analytics

Recent advanecs in augmented, mixed, and virtual reality, coupled with the need to perform analysis and decision-making on large-scale collections of volumetric images stimulate the research in immersive analytics.

Novelty and Anomaly Detection

Novelty and Anomaly Detection

Detecting the presence of outliers, like novelties or anomalies, with respect to a particular distribution has numerous applications in computer vision and in nearly every area of data science.

Recent Posts

CS678 Computer Vision - Fall 2021

6 minute read

Who When Where Instructor: Prof. Gianfranco Doretto Department of Computer Science and Electrical Engineering West Virginia University

WVU Spin-off Company Istovisio, Inc. Awarded Funding for Virtual Reality Research

less than 1 minute read

IstoVisio, Inc., a WVU spin-off company that created syGlass, has been awarded a National Institutes of Health Small Business Innovation Research grant total...

CS696 Machine Learning - Fall 2020

11 minute read

Who When Where Instructor: Prof. Gianfranco Doretto Department of Computer Science and Electrical Engineering West Virginia University

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

2 minute read

Stanislav Pidhorskyi, Ranya Almohsen, Donald A Adjeroh, Gianfranco Doretto