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Detection of Malaria Using CNN and Deep learning

EasyChair Preprint no. 12791

6 pagesDate: March 27, 2024


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

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  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}}
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