# Deep CNN frameworks comparison for malaria diagnosis

arXiv: https://arxiv.org/abs/1909.02829 · HTML: https://mlsanity.com/paper/1909.02829/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2019.

## Built on by (most cited first, 1 of 1)

- [End-to-end Malaria Diagnosis and 3D Cell Rendering with Deep Learning](https://mlsanity.com/paper/2108.04220/) (2021)

## Abstract (arXiv)

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.