Please use this identifier to cite or link to this item: http://repository.i3l.ac.id/jspui/handle/123456789/1054
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dc.contributor.authorLunoto, Dennis-
dc.date.accessioned2024-05-21T07:24:36Z-
dc.date.available2024-05-21T07:24:36Z-
dc.date.issued2024-01-31-
dc.identifier.urihttp://repository.i3l.ac.id/jspui/handle/123456789/1054-
dc.description.abstractLung cancer is the most malignant tumor with the highest mortality in the world. Early diagnosis and prognosis are important to improve the patient’s survival rate. With AI, screening which is one of the methods of detection is more sensitive and accurate allowing better analysis. This will in turn assist medical professionals in their line of work and improve the medical field overall. This research will explore a deep learning based on convolutional neural network (CNN), You Only Look Once (Yolo)’s Yolo5, LeNet5, as well as a transfer learning method using four EfficientNet models including EfficientNetB0, EfficientNetB1, EfficientNetB2, and EfficietNetB3.en_US
dc.language.isoenen_US
dc.publisherIndonesia International Institute for Life Sciencesen_US
dc.relation.ispartofseriesEP BI-002;EP24-040-
dc.subjectCNNen_US
dc.subjectLung canceren_US
dc.titleEfficientNet Based Detection of Lung Cancer Based on Histopathological Imageen_US
dc.typeThesisen_US
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