George Bebis

George Bebis

Foundation Professor
George Bebis
He, him, his
Biography

George Bebis is a Foundation Professor in the Department of Computer Science and Engineering (CSE) at the University of Nevada, Reno and Director of the Computer Vision Laboratory (CVL).

From 2013 to 2018, he served as department chair of CSE at the University of Nevada, Reno. His research interests include computer vision, image processing, pattern recognition, machine learning, and evolutionary computing. His research has been funded by NSF, NASA, ONR, NIJ, NDoT, Ford Motor Company, and Honda.

He is an associate editor of the Machine Vision and Applications Journal and serves on the editorial board of the International Journal on Artificial Intelligence Tools, the Pattern Analysis and Applications journal, and the Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization journal.

He has served on the program committees of various national and international conferences and the founder/main organizer of the International Symposium on Visual Computing (ISVC) and the International Symposium on Mathematical and Computational Oncology (ISMCO).

Education
  • Ph.D., Electrical and Computer Engineering, University of Central Florida, 1996
  • M.S, Computer Science, University of Crete, 1991
  • B.S, Mathematics, University of Crete, 1983

Prospective students

I am always looking for new self-motivated undergraduate and graduate students to join my research group. Basically, at a minimum, you'll need a GPA of 3.3 or higher and have good C, C++, and UNIX programming skills. Prior experience in image processing, computer vision, pattern recognition and machine learning is desirable. Must be hard working and eager to learn.

Learn more about our graduate programs 

Research interests

  • Computer vision
  • Image processing
  • Pattern recognition
  • Machine learning
  • Evolutionary computing

Selected publications

  • E. Emami, G. Bebis, A. Nefian, and T. Fong, Crater Detection Using Unsupervised Algorithms and Convolutional Neural Networks", IEEE Transactions on Geoscience and Remote Sensing, (accepted) 2019.
  • Touqeer Ahmad, Pavel Campr, Martin Cadik, and George Bebis Comparison of Semantic Segmentation Approaches for Horizon/Sky Line Detection", International Joint Conference on Neural Networks (IJCNN'17), Anchorage, Alaska, May 14-19, 2017.
  • Yongjie Chu, Touqeer Ahmad, George Bebis, Lindu Zhao, "Low-resolution face recognition with single sample per person", Signal Processing, vol. 141, pp. 144-157, 2017.
  • S. Khana, M, Hussain, H. Aboalsamhb, H. Mathkourb, G. Bebis, and M. Zakariahd, "Optimized Gabor features for mass classification in mammography", Applied Soft Computing, vol. 44, pp. 267-280, 2016.
  • Touqeer Ahmad, George Bebis, Emma Regentova, Ara Nefian, and T. Fong, "Coupling Dynamic Programming with Machine Learning for Horizon Line Detection", International Journal on Artificial Intelligence Tools, vol. 24, no. 4, pp. 1-19, 2015.
  • M. Jaberi, G. Bebis, M. Hussain, and G. Muhammad, Accurate and Robust Localization of Duplicated Region in Copy-Move Image Forgey", Machine Vision and Applications, vol. 25, pp. 451-475, 2014.
  • T. Uz, G. Bebis, A. Erol, and S. Prabhakar, "Minutiae-Based Template Synthesis and Matching for Fingerprint Authentication", Computer Vision and Image Understanding (CVIU), vol 113, pp. 979-992, 2009.
  • G. Amayeh, G. Bebis, A. Erol, and M. Nicolescu, "Hand-Based Verification and Identification Using Palm-Finger Segmentation and Fusion", Computer Vision and Image Understanding (CVIU) vol 113, pp. 477-501, 2009.
  • L. Loss, G. Bebis, M. Nicolescu, and A. Skurikhin, "An Iterative Multi-Scale Tensor Voting Scheme for Perceptual Grouping of Natural Shapes in Cluttered Backgrounds", Computer Vision and Image Understanding (CVIU) vol. 113, no. 1, pp. 126-149, January 2009.
  • W. Li, G. Bebis, and N. Bourbakis, "3D Object Recognition Using 2D Views", IEEE Transactions on Image Processing, vol. 17, no. 11, pp. 2236-2255, 2008.
  • Z. Sun, G. Bebis, and R. Miller, "On-road Vehicle Detection: A review", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 5, pp. 694-711, 2006.
  • Z. Sun, G. Bebis, and R. Miller, "Monocular Pre-crash Vehicle Detection: Features and Classifiers", IEEE Transactions on Image Processing , vol. 15, no. 7, pp. 2019-2034, July 2006.
  • Z. Sun, G. Bebis, and R. Miller, "On-Road Vehicle Detection Using Evolutionary Gabor Filter Optimization ", IEEE Transactions on Intelligent Transportation Systems, vol. 6, no. 2, pp. 125-137, 2005.
  • Z. Sun, G. Bebis, and R. Miller, "Object Detection Using Feature Subset Selection", Pattern Recognition, vol. 37, pp. 2165-2176, 2004.
  • G. Bebis. D. Egbert, and M. Shah, "Review of Computer Vision Education", IEEE Transactions on Education, vol. 46, no. 1, pp. 2-21, 2003.
  • G. Bebis. S. Louis, Y. Varol, and A. Yfantis, "Genetic Object Recognition Using Combinations of Views", IEEE Transactions on Evolutionary Computation, vol 6, no. 2, pp. 132-146, April 2002.
  • G. Bebis, M. Georgiopoulos, M. Shah, and N. da Vitoria Lobo, " Indexing Based on Algebraic Functions of Views", Computer Vision and Image Understanding (CVIU), Vol. 72, No. 3, pp. 360-378, 1998.

Courses taught

  • CS302 - Data Structures
  • CS485/685 - Computer Vision
  • CS 201 - Computer Science I
  • CS791Y - Topics in Computer Vision
  • CS480/680 - Computer Graphics
  • CS 479/679 Pattern Recognition
  • CS 477/677 - Analysis of Algorithms
  • CS791S - Neural Networks
  • CS491Q/790Q - SEM: Machine Learning (Biometrics)
  • CS491Y/791Y Mathematical Methods for Computer Vision
  • CS365 - Mathematics of Computer Science
  • CS474/674 - Image Processing and Interpretation
  • CS773C - Machine Intelligence (Object Recognition)