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2. ENGINEERING AND TECHNOLOGY
Abstract 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 unstrained images.
Pattanaik, P, Wang, Z. & Horain, P. (2019). Deep CNN frameworks comparison for malaria diagnosis. IMVIP 2019: Irish Machine Vision & Image Processing, Technological University Dublin, 28-30 August. doi:10.21427/t6bj-zr14