IVSep 6, 2019
Deep CNN frameworks comparison for malaria diagnosisPriyadarshini Adyasha Pattanaik, Zelong Wang, Patrick Horain
We compare Deep Convolutional Neural Networks (DCNN) frameworks, namely AlexNet and VGGNet, for the classification of healthy and malaria-infected cells in large, grayscale, low quality and low resolution microscopic images, in the case only a small training set is available. Experimental results deliver promising results on the path to quick, automatic and precise classification in unstained images.