Detection of Malaria Using CNN and Deep learning

EasyChair Preprint no. 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, deep learning, MobileNetV2, neural network, ResNet50, VGG19

@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 no. 12791},

  year = {EasyChair, 2024}}