Skripsi

KOMBINASI SEGMENTASI PRE DAN POST IVA UNTUK PENINGKATAN KINERJA DETEKSI LESI PRA KANKER

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Penilaian

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Cervical cancer is one of the leading causes of death among women, particularly in developing countries. Early detection through Visual Inspection with Acetic Acid (VIA) is considered effective, but it still presents a high rate of false positives due to the limitations of visual observation. This study aims to develop and evaluate the YOLOv8 model for accurate and efficient segmentation of pre- and post-VIA images to minimize false positives. Each variant of YOLOv8 was trained using different hyperparameter configurations, specifically batch size and optimizer types. Model evaluation was conducted by measuring performance metrics and comparing each YOLOv8 variant to determine the best model. Finally, unseen testing was performed to assess the model's generalization and object detection capability on previously unseen data samples. Based on the evaluation results, the best-performing model was YOLOv8m-seg with a batch size of 8 and the Adam optimizer.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507004108	T1785642	T1785642025	Central Library (REFERENCE)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1785642025

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvi, 125 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

TUTI

Other version/related

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