Detection of Malaria Using CNN and Deep learning

EasyChair Preprint 12791

Abstract

Detection of malaria Parasite from the blood images which contain a dataset of 27000 images using different cnn models and deep learning techniques. We design the automatic parasite detection in blood from Giemsa-stained smears using three CNN pre-trained models such as VGG19, ResNet50, and MobileNetV2. As the CNNs are poorly performing for small datasets, we introduce the transfer learning technique.

Keyphrases: CNN, MobileNetV2, ResNet50, VGG19, deep learning, neural network

@booklet{EasyChair:12791,
  author    = {Manipal Reddy and Bhargav Ram and Krishna Chaitanya and Simhadri Reddy},
  title     = {Detection of Malaria Using CNN and Deep learning},
  howpublished = {EasyChair Preprint 12791},
  year      = {EasyChair, 2024}}