Deep Learning and Computational Neuroscience

 

Deep Learning and Computer Vision Lab aims to conduct research on cutting-edge topics such as deep learning and computer vision. Research projects range from the evaluation of systems from a human perspective to the development of new algorithms and methods for technical issues. Furthermore, experiments on remote and non-destructive image acquisition methods are carried out in the laboratory to observe the challenges which are faced in real data problems. Our research is mainly oriented towards the following areas:

  • Object detection
  • Contentious attacks
  • Medical image processing
  • 3D model development
  • Manufacturer models
  • GPU programming

 

 

 

 

 

 

 

 

yayın-1

A Dimension Reduction Approach to Player Rankings in European Football

Ayse Elvan Aydemir; Tugba Taskaya Temizel; Alptekin Temizel; Kliment Preshlenov; Daniel M. Strahinov

24 August 2021

yayın-2

GPU accelerated 3DES encryption

Kaan Furkan Altınok, Afşin Peker, Cihangir Tezcan, Alptekin Temizel

21 July 2021

yayın-4

Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy

S. Ali, M. Dmitrieva, N. Ghatwary, S. Bano, G. Polat, A. Temizel

May 2021

yayın-5

Multi-modal egocentric activity recognition using multi-kernel learning

Mehmet Ali Arabacı, Fatih Özkan, Elif Surer, Peter Jančovič, Alptekin Temizel

28 April 2020

yayın-6

Imperceptible Adversarial Examples by Spatial Chroma-Shift

Ayberk Aydin, Deniz Sen, Berat Tuna Karli, Oguz Hanoglu, Alptekin Temizel

22 October 2021

yayın-7

Generative Data Augmentation for Vehicle Detection in Aerial Images

Hilmi Kumdakcı, Cihan Öngün, Alptekin Temizel

Jan. 2021