Siddhivinayak Kulkarni

Dr. Siddhivinayak Kulkarni (Sid) is currently working as a Senior Lecturer at the University of Ballarat. Prior to that, he was working as an Assistant Professor at Nipissing University, Canada. In 2007 and 2008, he organized workshops in Australia on Machine Learning and Algorithms, and attracted many research papers from various countries. Dr. Kulkarni has served on organizing and program committees for more than twenty-five conferences organized in various countries at an International level. He has served an editorial board member and reviewer for many reputed journals. He has published significant papers in reputable peer reviewed journals and presented papers at international conferences. His research interests include machine learning/computational intelligence, as well as pattern recognition and its application in image/video retrieval, biometrics, and health informatics.


Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques
Siddhivinayak Kulkarni. © 2012. 464 pages.
Machine learning is an emerging area of computer science that deals with the design and development of new algorithms based on various types of data. Machine Learning Algorithms...
Machine Learning Approach for Content Based Image Retrieval
Siddhivinayak Kulkarni. © 2012. 11 pages.
Developments in technology and the Internet have led to an increase in number of digital images and videos. Thousands of images are added to WWW every day. Content based Image...
Emergence Phenomenon and Fuzzy Logic in Meaningful Image Segmentation and Retrieval
Sagarmay Deb, Siddhivinayak Kulkarni. © 2012. 12 pages.
Content-based image retrieval is a difficult area of research in multimedia systems. The research has proven extremely difficult because of the inherent problems in proper...
Neural Networks for Content-Based Image Retrieval
Brijesh Verma, Siddhivinayak Kulkarni. © 2007. 21 pages.
This chapter introduces neural networks for Content-Based Image Retrieval (CBIR) systems. It presents a critical literature review of both the traditional and neural network...