Classification of Malaria Cell Image using Inception-V3 Architecture

Malaria is a severe global public health problem caused by the bite of infected mosquitoes. It can be cured, but only with early detection and effective, quick treatment. cause conditions if not properly diagnosed treated at an stage. In worst scenario, it death. This study aims focusing on classifying malaria cell images. classified as dangerous disease female Anophles mosquito. As such, leads to mortality when immediate action treatment fails administered. particular, this classify images utilizing Inception-V3 architecture. study, training was conducted 27,558 image data through architecture proposing 3 scenarios. The proposed scenario 1 model applies SGD optimizer generate loss value 0.13 accuracy 0.95; 2 Adam 0.09 0.96; lastly implements RMSprop 0.08 0.97. Applying three scenarios, results apparently indicate that using capable providing best 97% lowest value, compared 2. Further, test confirms in cells effectively.