With the proliferation of multimedia data and evergrowing requests for multimedia applications, new challenges are emerged for efficient and effective managing and accessing large...
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
In this work we investigate the feasibility and effectiveness of unsupervised tissue clustering and classification algorithms for DTI data. Tissue clustering and classification ...
There are many studies on ABS and several frameworks for ABS have already been published. However, there are few frameworks that can enable agent-based simulation using large numb...
We describe a novel framework for class noise mitigation that assigns a vector of class membership probabilities to each training instance, and uses the confidence on the current ...