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Image of DETEKSI LESI PRA-KANKER SERVIKS PADA CITRA KOLPOSKOPI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR YOLO

Skripsi

DETEKSI LESI PRA-KANKER SERVIKS PADA CITRA KOLPOSKOPI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR YOLO

Nurqolbiah, Fatihani - Personal Name;

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Deteksi lesi pra-kanker serviks memegang peran krusial dalam menganalisis citra medis untuk diagnosa yang tepat. Keterbatasan pengamatan visual mendorong perlunya deteksi berbasis komputer. Penelitian ini mengusulkan model deteksi lesi pra-kanker serviks menggunakan Convolutional Neural Network (CNN) dengan arsitektur YOLO, memberikan akurasi yang tinggi. Dua dataset digunakan, pertama dari IARS Cervical Cancer Image Bank (Dataset 1) dengan 913 gambar dari 200 kasus, dan kedua dari Rumah Sakit Mohammad Hoesin Palembang (Dataset 2) dengan 160 gambar. Hasil evaluasi matriks menunjukkan bahwa YOLOv8 menjadi model terbaik dengan mAP50 sebesar 92% pada Dataset 1, 78,4% pada Dataset 2, dan 81,5% pada gabungan kedua dataset.


Availability
Inventory Code Barcode Call Number Location Status
2407001531T140608T1406082024Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T1406082024
Publisher
Inderalaya : Prodi Magister Ilmu Komputer, Fakultas Ilmu Komputer, Universitas Sriwijaya., 2024
Collation
xiv, 71 hlm.; Ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
006.307
Content Type
Text
Media Type
unmediated
Carrier Type
-
Edition
-
Subject(s)
Sistem Pakar
Prodi Magister Ilmu Komputer
Specific Detail Info
-
Statement of Responsibility
SEPTA
Other version/related

No other version available

File Attachment
  • DETEKSI LESI PRA-KANKER SERVIKS PADA CITRA KOLPOSKOPI MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DENGAN ARSITEKTUR YOLO
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