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MalariaCLass

Binary Image Classification with Tensorflow and EfficientNetB0 pre-trained model
And an other copy with Tensorflow and ResNet50 pre-trained model
This repo is a binary classification project that identify cells images as parasitized or uninfected cells from the thin blood smear slide images of segmented cells.

Prerequisites

Python 3.x Tensorflow 2.x

Datasets

The Malaria dataset contains a total of 27,558 cell images with equal instances of parasitized and uninfected
size:337.08 MiB
On Tensorflow Datasets Catalog:Malaria
The National Library of medecin:NLM

Model

EfficientNetB0 pre-trained model with 5,330,571 parameters
its size: 29 MB
Documentation
ResNet50 pre-trained model with 25,636,712 parameters
its size: 98 MB
Documentation

Cells Segmentation

Cells segmentation with detectron2 and Mask R-CNN
Detectron2

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Binary Image Classification with EfficientNetB0

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