Artificial Intelligence, Machine Learning and Computer Vision Research Group
Artificial Intelligence is a field that deals with the development of intelligent machines and software. We are working on the solutions of optimization problems with metaheuristics, Swarm Intelligence methods and especially Genetic Algorithms.
Within the scope of Machine Learning, we provide solutions to problems by using Artificial Neural Networks as well as other estimation methods and classifiers. We also apply Machine Learning methods in computer vision / image processing fields. Deep learning models, which have achieved serious success as a sub-field of machine learning in recent years; We also continue to work on intelligent systems that combine two or more artificial intelligence methods.
Research Topics
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Intelligent Systems
- Optimization
- Computer Vision
- Wireless Sensor Networks
- Swarm Intelligence
- Computer Graphics
Faculty Members:
- Prof. Dr. Aybars UĞUR
Research Assistants:
- Arş. Gör. Dr. Osman GÖKALP
- Arş. Gör. Dr. Arif Erdal TAŞCI
- Arş. Gör. Sema BODUR
PhD Students:
- Caner ULUTÜRK
- Tunç GÜLTEKİN
- Enes ATEŞ
- Yiğitcan ŞENER
RECENT DATE PROJECTS
1) Development of a Metaheuristics Based Java Script Library for Solving Continuous Optimization Problems
BAP Research Project, 2016-2017 (19 months) (16-MUH-072)
Director: Prof. Dr. Aybars UGUR
Researchers: Res. See. Dr. Osman GÖKALP, Res. See. Sema BODUR.
Project outputs:
(Referred National Journal Full Text) Gökalp O., Uğur A., Bodur S., "CONTOPT-JS: A JavaScript Software Library based on Metaheuristic Algorithms for Continuous Optimization Problems", Journal of Intelligent Systems and Applications, Vol: 1, Issue: 2 , pages 168-174, 2018. (This study was presented at the ASYU-2017 Conference and published only in summary in the Book of Proceedings (ISBN: 978-605-84722-8-0).)
Project website: http://yzgrafik.ege.edu.tr/~ugur/contopt_js/
2) Image Classification with Deep and Community Learning Approaches
BAP Research Project, 2018-Ongoing (18-MUH-001)
Executive : Prof. Dr. Aybars UGUR
Researchers : Res. See. Dr. Arif Erdal TAŞCI, PhD Student Caner ULUTÜRK
Project Outputs:
Taşcı E., Uğur A., "Image classification using ensemble algorithms with deep learning and hand-crafted features", 26th Signal Processing and Communications Applications Conference (SIU), İZMİR, TURKEY, 2-5 May 2018, pp.1-4 (Full text oral presentation)
PREVIOUS PROJECTS
1) Development of Field Priority Estimation and Sensor Placement Optimization Methods in 113E947 Satellite Images
Tubitak 3001 Project, 2014-2015
Manager : Assoc. Dr. Aybars UGUR
Researcher: Assist. Assoc. Dr. Tahir Emre KALAYCI
Scholars: Enes ATEŞ, Res. See. Osman GÖKALP, Yiğitcan ŞENER
2) Development of Software that Combines Rectangular Photo Pieces Using Artificial Intelligence and Image Processing Methods
BAP Research Project, 2012-2013
Director: Assoc. Dr. Aybars UGUR
Researcher: Res. See. Arif Erdal TAŞCI
3) Developing a Software Classifying Leaves According to Their Quality with Artificial Neural Networks and Image Processing Methods
BAP Research Project, 2011-2012
Director: Assoc. Dr. Aybars UGUR
Researcher: Res. See. Osman GÖKALP, Caner ULUTÜRK
SELECTED SCI ARTICLES
- Yildirim K., Ugur Aybars, Kinaci A. (2007). Design and Implementation of a Software Presenting Information in DVB Subtitles in Various Forms. IEEE Transactions on Consumer Electronics, 53(4), 1656-1660., Doi: 10.1109/TCE.2007.4429266
- UĞUR AYBARS (2008). Path planning on a cuboid using genetic algorithms. INFORMATION SCIENCES, 178(16), 3275-3287., Doi: 10.1016/j.ins.2008.04.005
- UĞUR AYBARS, AYDIN DOĞAN (2009). An interactive simulation and analysis software for solving TSP using Ant Colony Optimization algorithms. Advances in Engineering Software, 40(5), 341-349., Doi: 10.1016/j.advengsoft.2008.05.004
- Ugur Aybars, Kinaci Ahmet Cumhur (2010). A web based tool for teaching neural network concepts. Computer Applications in Engineering Education, 18(3), 449-457., Doi: 10.1002/cae.20184
- Gürünlü Alma Özlem, Kurt Serdar, Uǧur Aybars (2011). Genetic algorithms for outlier detection in multiple regression with different information criteria. Journal of Statistical Computation and Simulation, 81(1), 29-47., Doi: 10.1080/00949650903136782
- KALAYCI TAHİR EMRE, UĞUR AYBARS (2011). GENETIC ALGORITHM BASED SENSOR DEPLOYMENT WITH AREA PRIORITY. Cybernetics and Systems, 42(8), 605-620., Doi: 10.1080/01969722.2011.634676
- Ugur Aybars, Aydin Dogan (2012). IMPROVING PERFORMANCE OF ACO ALGORITHMS USING CROSSOVER MECHANISM BASED ON BEST TOURS GRAPH. INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 8(4), 2789-2802.
- TAŞCI ARİF ERDAL, UĞUR AYBARS (2015). Shape and Texture Based Novel Features for Automated Juxtapleural Nodule Detection in Lung CTs. Journal of Medical Systems, 39(5), 1-13., Doi: 10.1007/s10916-015-0231-5
- ATEŞ ENES, KALAYCI TAHİR EMRE,UĞUR AYBARS (2017). Area-priority-based sensor deployment optimisation with priority estimation using K-means. IET Communications, 11(7), 1082-1090., Doi: 10.1049/iet-com.2016.1264
- AFŞAR BEKİR, AYDIN DOĞAN, UĞUR AYBARS, KORUKOĞLU MUSTAFA SERDAR (2017). Self-Adaptive and Adaptive Parameter Control in Improved Artificial Bee Colony Algorithm. INFORMATICA, 28(3), 415-438., Doi: http://dx.doi.org/10.15388/Informatica.2017.136 (Yayın No: 3680960)
SELECTED PAPERS (EXCEPT THE PRODUCTION FROM PROJECTS AND SUBMISSIONED IN THE LAST 2 YEARS)
- Taşcı A.E., Gökalp O., Uğur A., "Development of a novel feature weighting method using CMA-ES optimization", 2018 26th Signal Processing and Communications Applications Conference (SIU), Izmir, Turkey, TÜRKIYE,
- Gökalp O., Uğur A., "An Order Based Hybrid Metaheuristic Algorithm for Solving Optimization Problems", 2017 International Conference on Computer Science and Engineering (UBMK), ANTALYA, TÜRKIYE, 5-8 Ekim 2017,
- Gültekin T., Uğur A., "An iterative dynamic ensemble weighting approach for deep learning applications", 2017 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, TÜRKIYE,
