Publications | Computer Vision Research Group (CVRG)

Thesis

Posted on 01 Jan 2021 by CVRG

National Conference Publications

Posted on 01 Jan 2021 by CVRG

Elimination of Useless Images from Raw Camera-Trap Data

Posted on 01 Jan 2019 by CVRG

Affordable person detection in omnidirectional cameras using radial integral channel features

Posted on 01 Jan 2019 by CVRG

Training convolutional neural networks with image patches for object localisation

Posted on 01 Jan 2017 by CVRG

Semih Orhan

Research interests:

Machine Learning
Computer Vision

Ph.D. : Computer Engineering, Izmir Institute of Technology (ongoing)

Yagiz Nalcakan

Yağız Nalçakan received his B.Sc. degree from Trakya University and he received M.Sc. degree from Istanbul University – Cerrahpasa. Currently, he is a Ph.D. student at Izmir Institute of Technology.

Research Interests:

Computer Vision
Deep Learning

B.Sc. : Computer Engineering, Trakya University (2015)

M.Sc. : Computer Engineering, Istanbul University (2019)

Ph.D. : Computer Engineering, Izmir Institute of Technology (ongoing)

Yalin Bastanlar

I studied civil engineering at the Middle East Technical University (METU) and obtained B.S. degree in 2001. I joined METU Informatics Institute for my graduate studies where I started to work on computer vision. I obtained M.S. and Ph.D. degrees from the Information Systems Department of Informatics Institute in April 2005 and July 2009, respectively. During my Ph.D. studies, I mostly worked on 3D computer vision especially when omnidirectional cameras are included. I was with the Perception Group at INRIA Rhone-Alpes as a visiting researcher for six months in 2008. I conducted a post-doctoral research visit to Oxford Brookes Vision Group in 2010. In 2011, I started as an Assistant Professor at the Department of Computer Engineering, Izmir Institute of Technology. In 2017, I became an Associate Professor at the same department.

Research Interests:
· 3D reconstruction from images
· Calibration and epipolar geometry of omnidirectional cameras
· Object detection/classification using cameras
· Vision for robots, visual odometry
· Machine learning for machine vision