Professor Volkan Isler

Twin Cities
Project Title: 
Optimization and Learning Algorithms for Computer Vision Tasks for Environmental Monitoring Projects

These researchers are using deep learning-based approaches to solve many relevant computer vision problems that come up in environmental monitoring tasks. The first such problem is concerned with estimating the number, size, and location of fruits in apple orchards. In particular, the researchers study the problem of how to accurately detect and count fruits under uncontrolled environmental conditions. Training any modern network architecture in a feasible amount of time has become infeasible even for modern machines with high-end graphics cards. The group is using the Mesabi cluster, with its large GPU memory footprints, to train their models.

Project Investigators

Jun-Jee Chao
Wenbo Dong
Kazim Selim Engin
Burak Mert Gonultas
Nicolai Haeni
Professor Volkan Isler
Raunak Manekar
Pravakar Roy
Jiacheng Yuan
 
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