# Deep CNN frameworks comparison for malaria diagnosis

**Authors:** Priyadarshini Adyasha Pattanaik, Zelong Wang, Patrick Horain  
**arXiv:** [1909.02829](https://arxiv.org/abs/1909.02829)  
**Date:** 2019-09-06  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/1909.02829v1/

## 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 unstained images.