Deep CNN frameworks comparison for malaria diagnosis
Priyadarshini Adyasha Pattanaik, Zelong Wang, Patrick J. Horain · arXiv (Cornell University) · 2019
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.