Abstract
Conference Title: 2016 24th European Signal Processing Conference (EUSIPCO) Conference Start Date: 2016, Aug. 29 Conference End Date: 2016, Sept. 2 Conference Location: Budapest, Hungary Automatic classification of human epithelial type-2 (HEp-2) cells can improve the diagnostic process of autoimmune diseases (ADs) in terms of lower cost, faster response, and better repeatability. However, most of the proposed methods for classification of HEp-2 cells suffer from several constraints including tedious parameter tuning, massive memory requirement, and high computational costs. We propose an adaptive distributed dictionary learning (ADDL) method where the dictionary learning problem is reformulated as a distributed learning task. With the help of this approach, we develop an automatic and robust method that effectively handles the complexity of the problem in terms of memory and computational cost and also obtains superior classification accuracy.