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A deep learning based lightweight Computer Aided Diagnostic System with an aim of easing the weary task of detection of Malaria infected cells by examination of blood smears under microscope and to enable the practical use of the model in remote and rural areas where high computation power and network may or may not be available.

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Malaria Detection (Models & Web App)

Malaria is a mosquito-borne life-threatening disease caused by five species of Plasmodium parasites (single-celled organisms).

Mosquito-Net

A deep learning based lightweight Computer Aided Diagnostic System with an aim of easing the weary task of detection of Malaria infected cells by examination of blood smears under microscope and to enable the practical use of the model in remote and rural areas where high computation power and network may or may not be available.

Public Repository in spirit of World Malaria Day - 25th April.

Mosquito-Net (Mish version)

Mosquito net with a different activation function Mish. Slightly improved performance.

Mosquito-Net V2 (Mobile version)

A more optimized version of MosquitoNet with Depthwise Seperable Convolutions for mobile devices accepted & presented inICML 2020, MLGH Workshop Poster

Note

As COVID-19 spreads rapidly around the globe, there is an urgent need to aggressively tackle the novel coronavirus while ensuring that other killer diseases, such as malaria, are not neglected. WHO urges countries to ensure the continuity of malaria services in the context of the pandemic, provided that best practices to protect health workers and communities are followed. Find more at https://www.who.int/malaria/areas/epidemics_emergencies/covid-19/en/

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A deep learning based lightweight Computer Aided Diagnostic System with an aim of easing the weary task of detection of Malaria infected cells by examination of blood smears under microscope and to enable the practical use of the model in remote and rural areas where high computation power and network may or may not be available.

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