PawarMukesh/MalariaCell-Detector
Malaria cell Binary Classification Probelm, Build DL Model USing Transfer learning technique.
This project helps medical professionals or lab technicians quickly identify malaria infections from microscope images. You input digital images of red blood cells, and it outputs a classification indicating whether the cells are 'Parasitized' (infected with malaria) or 'Uninfected'. It's designed for anyone performing diagnostic screening in a clinical or research lab setting.
No commits in the last 6 months.
Use this if you need an automated system to classify red blood cell images as malaria-infected or uninfected, speeding up the diagnostic process.
Not ideal if you need to detect other bloodborne diseases or require a nuanced diagnosis beyond a simple malaria positive/negative.
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Jupyter Notebook
License
MIT
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Last pushed
Oct 14, 2022
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