Deep CNN frameworks comparison for malaria diagnosis

Autor:	Pattanaik, Priyadarshini Adyasha, Wang, Zelong, Horain, Patrick
Rok vydání:	2019
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition Computer Science - Machine Learning
Zdroj:	IMVIP 2019 Irish Machine Vision and Image Processing Conference, Sep 2019, Dublin, Ireland
Druh dokumentu:	Working Paper
Popis:	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.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1909.02829 Zobrazit plný text záznamu View this record from Arxiv