Communication Dans Un Congrès Année : 2019

Deep CNN frameworks comparison for malaria diagnosis

Résumé

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.

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hal-02280412 , version 1 (06-09-2019)

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Priyadarshini Adyasha Pattanaik, Zelong Wang, Patrick Horain. Deep CNN frameworks comparison for malaria diagnosis. IMVIP 2019 Irish Machine Vision and Image Processing Conference, Aug 2019, Dublin, Ireland. ⟨hal-02280412⟩
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