Efektivitas Transfer Learning Dalam Pendeteksian Penyakit Pneumonia Melalui Citra X-Ray Paru Manusia
Abstract
Pneumonia is a disease that attacks the human lung system. This disease causes serious problems not only in Indonesia but is a serious problem for people around the world. By doing early detection of pneumonia can reduce mortality. X-ray imaging of the human chest is one of the most widely used to diagnose pneumonia. The X-ray method is a fast and easy method of detecting a disease. In this study, the Transfer Learning method was used to classify chest X-ray images labeled as non-pneumonia and pneumonia lungs. To classify this image recognition, the Google Collaboratory application uses the ResNet50V2 Architecture model. The dataset used for this study was 5863 training data by testing 30 times, the results obtained were an accuracy of 97% and a loss value of 0.4.
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