Refereed Publications (in reverse chronological order)
Journal (
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    		•  Conference Proceedings (
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    • C. H. Li, I. Gondra, and L. Liu. An Efficient Parallel Neural Network-Based Multi-Instance Learning Algorithm. The Journal of Supercomputing (Springer). In Press.
       
    • F. I. Alam and I. Gondra. A Bayesian Network-based Tunable Image Segmentation Algorithm for Object Recognition. Proceedings of IEEE International Symposium on Signal Processing and Information Technology (ISSPIT'11), pp. 11-16, Bilbao, Spain, December 2011.
       
    • T. Xu and I. Gondra. A Simple and Effective Texture Characterization for Image Segmentation. Signal, Image and Video Processing (Springer). In Press.
       
    • T. Xu, I. Gondra, and D. Chiu. Adaptive Kernel Diverse Density Estimate for Multiple Instance Learning. Proceedings of 2011 International Conference on Machine Learning and Data Mining (ICDM'11), New York, NY, USA, August/September 2011. Springer Lecture Notes in Computer Science. vol.  6871, pp. 185-198.
       
    • M. Cormier and I. Gondra. Supervised Object Segmentation Using Visual and Spatial Features. Proceedings of the 2011 International Conference on Image Processing, Computer Vision and Pattern Recognition (IPCV'11), pp. 557-563, Las Vegas, Nevada, USA, July 2011.
    • I.Gondra and T. Xu. Image Region Re-Weighting via Multiple Instance Learning. Signal, Image and Video Processing (Springer). vol. 4, no. 4, pp. 409-417, November 2010.
       
    • C. H. Li and I. Gondra. A Novel Neural Network-Based Approach for Multiple Instance Learning. Proceedings of the Tenth IEEE International Conference on Computer and Information Technology (CIT’10), pp. 451-456, Bradford, UK, June 2010.
       
    • I. Gondra and T. Xu. A Multiple Instance Learning Based Framework for Semantic Image Segmentation. Multimedia Tools and Applications (Springer), vol. 48, no. 2, pp. 339-365, April 2010.
       
    • T. Xu and I. Gondra. Texture Map: An Effective Representation for Image Segmentation. Proceedings of the C3S2E Conference (C3S2E’09), pp. 197-203, ACM, Montreal, Canada, May 2009.
       
    • I. Gondra and T. Xu. Adaptive Mean Shift-Based Image Segmentation Using Multiple Instance Learning. Proceedings of the Third IEEE International Conference on Digital Information Management (ICDIM'08), pp. 716-721, London, UK, November 2008.
       
    • R. Fernandes de Mello and I. Gondra. Multi-Dimensional Dynamic Time Warping for Image Texture Similarity. Proceedings of the Nineteenth Brazilian Symposium on Artificial Intelligence (SBIA'08), Salvador, Bahia, Brazil, October 2008. Springer Lecture Notes in Computer Science. vol. 5249, pp. 23-32.
       
    • I. Gondra and D. R. Heisterkamp. Content-Based Image Retrieval with The Normalized Information Distance. Computer Vision and Image Understanding (Elsevier), vol. 111, no. 2, pp. 219-228, August 2008.
       
    • T. Xu and I. Gondra. An Objective Evaluation of the Mean Shift-Based Image Segmentation Algorithm. Proceedings of the 2008 International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV'08), pp. 205-211, Las Vegas, Nevada, USA, July 2008.
       
    • I. Gondra. Applying Machine Learning to Software Fault-Proneness Prediction. Journal of Systems and Software, Special Issue on Model-Based Software Testing (Elsevier), vol. 81, no. 2, pp. 186-195, February 2008.
    • T. F. Hu, I. Gondra, H. C. Su, and C. C. Chang. Forecasting Inflation Under Globalization with Artificial Neural Network-Based Thin and Thick Models. Proceedings of the 2007 International Conference on Soft Computing and Applications (ICSCA'07) (in conjunction with the 2007 World Congress on Engineering and Computer Science), pp. 909-914, San Francisco, California, USA, October 2007.
       
    • I. Cabria and I. Gondra. Predicting Properties by Exploiting Their Relationships. Proceedings of the 2007 International Conference on Engineering and Mathematics (ENMA'07), pp. 125-131, Bilbao, Spain, July 2007.
       
    • T. F. Hu, I. Gondra, and H. C. Su. Forecasting Daily Stock Returns of East Asian Tiger Countries with Intermarket Influences: A Comparative Study on Artificial Neural Networks and Conventional Models. Proceedings of the 2007 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'07), pp. 836-842, Las Vegas, Nevada, USA, June 2007.
       
    • T. F. Hu, H. C. Su, and I. Gondra. Examining Nonlinear Interrelationships Among Foreign Exchange Markets in the Pacific Basin with Artificial Neural Networks. Proceedings of the 2007 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'07), pp. 829-835, Las Vegas, Nevada, USA, June 2007.
       
    • I. Gondra. Region-Based Latent Semantic Indexing of an Image Database. WSEAS Transactions on Computers, vol. 6, no. 4, pp. 650-655, April 2007.
       
    • I. Gondra and D. R. Heisterkamp. A Kolmogorov Complexity-Based Normalized Information Distance for Image Retrieval. Proceedings of the 2005 International Conference on Imaging Science, Systems, and Technology (CISST'05), pp. 3-7, Las Vegas, Nevada, USA, June 2005.
       
    • I. Gondra and D. R. Heisterkamp. Semantic Similarity for Adaptive Exploitation of Inter-Query Learning. Proceedings of the 2004 International Conference on Computing, Communications, and Control Technologies (CCCT'04) (sponsored by the University of Texas at Austin), vol. 1, pp. 142-147, Austin, Texas, USA, August 2004.
       
    • I. Gondra and D. R. Heisterkamp. Learning in Region-Based Image Retrieval with Generalized Support Vector Machines. Proceedings of the Fourth International Workshop on Multimedia Data and Document Engineering (MDDE'04) (in conjunction with IEEE Conference on Computer Vision and Pattern Recognition (CVPR'04)), Washington, DC, USA, July 2004.
       
    • I. Gondra and D. R. Heisterkamp. Probabilistic Region Relevance Learning for Content-Based Image Retrieval. Proceedings of the 2004 International Conference on Imaging Science, Systems, and Technology (CISST'04), pp. 434-440, Las Vegas, Nevada, USA, June 2004.
       
    • I. Gondra, D. R. Heisterkamp, and J. Peng. Improving Image Retrieval Performance by Inter-Query Learning with One-Class Support Vector Machines. Neural Computing & Applications (Springer), vol. 13, no. 2, pp. 130-139, June 2004.
       
    • I. Gondra and D. R. Heisterkamp. Summarizing Inter-Query Knowledge in Content-Based Image Retrieval via Incremental Semantic Clustering. Proceedings of the Fifth IEEE International Conference on Information Technology (ITCC'04), vol. 2, pp. 18-22, Las Vegas, Nevada, USA, April 2004.
       
    • I. Gondra and D. R. Heisterkamp. Adaptive and Efficient Image Retrieval with One-Class Support Vector Machines for Inter-Query Learning. WSEAS Transactions on Circuits and Systems, vol. 3, no. 2, pp. 324-329, April 2004.
       
    • I. Gondra, D. R. Heisterkamp, and J. Peng. Improving the Initial Image Retrieval Set by Inter-Query Learning with One-Class SVMs. Proceedings of the Third International Conference on Intelligent Systems Design and Applications (ISDA'03), Tulsa, Oklahoma, USA, August 2003. Springer Advances in Intelligent and Soft Computing. vol. 23, pp. 393-402.
       
    • A. Auyeung, I. Gondra, and H. K. Dai. Integrating Random Ordering into Multi-heuristic List Scheduling Genetic Algorithm. Proceedings of the Third International Conference on Intelligent Systems Design and Applications (ISDA'03), Tulsa, Oklahoma, USA, August 2003. Springer Advances in Intelligent and Soft Computing. vol. 23, pp. 447-458.
       
    • I. Gondra and M. H. Samadzadeh. A Coarse-Grain Parallel Genetic Algorithm for Finding Ramsey Numbers. Proceedings of the Eighteenth Annual ACM Symposium on Applied Computing (SAC'03), pp. 2-8, Melbourne, Florida, USA, March 2003.
       
    • A. AuYeung, I. Gondra, and H. K. Dai. Multi-heuristic List Scheduling Genetic Algorithm for Task Scheduling. Proceedings of the Eighteenth Annual ACM Symposium on Applied Computing (SAC'03) , pp. 721-724, Melbourne, Florida, USA, March 2003.
     
     Book Chapters
    • T. F. Hu, I. Gondra, H. C. Su, and C. C. Chang. Forecasting Inflation with the Influence of Globalization using Artificial Neural Network-based Thin and Thick Models. In S. I. Ao, B. Rieger and S. S. Chen (Eds.), Advances in Computational Algorithms and Data Analysis, Lecture Notes in Electrical Engineering, Vol. 14, pp. 563-575, Springer, 2008.
       
    • I. Gondra. Personalized Content-Based Image Retrieval. In R. A. Gonzalez, N. Chen and A. Dahanayake (Eds.), Personalized Information Retrieval and Access: Concepts, Methods and Practices, pp. 194-219. IGI Publishing, 2008.
       
    • I. Gondra. Parallelizing Genetic Algorithms: A Case Study. In D. Vrakas and I. Vlahavas (Eds.), Artificial Intelligence for Advanced Problem Solving Techniques, pp. 284-307. IGI Publishing, 2008.
     
     Non-Refereed Publications
    • M. Cormier and I. Gondra. “Strong Image Segmentation Using Learned Regions and Spatial Relationships”. In APICS Annual Computer Science Conference, Saint Mary's University, Halifax, Nova Scotia, Canada, October 2010.
       
    • M. Cormier and I. Gondra. “Strong Image Segmentation through Non-homogeneous Region Merging”. In APICS Annual Computer Science Conference, Dalhousie University, Halifax, Nova Scotia, Canada, October 2009.
     Theses
    • I. Gondra. Inter-Query Learning in Content-Based Image Retrieval. Ph.D. Dissertation, Oklahoma State University, Stillwater, Oklahoma, USA, July 2005.
       
    • I. Gondra. A Coarse-Grain Parallel Genetic Algorithm to Improve the Bounds of Some Ramsey Numbers. Master Thesis, Oklahoma State University, Stillwater, Oklahoma, USA, May 2002.