Skripsi

KLASIFIKASI SUDUT PANDANG JANTUNG JANIN DARI MEDIA ULTRASONOGRAPHY MEGGUNAKAN CONVOLUTIONAL NEURAL NETWORK

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Penilaian

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Heart is a vital organ in human body, however congengital heart disease is an anomaly in fetal body structure that frequently happens, because of that fetal echocardiograph is done by pediatric cardiologist to identify the congengital heart disease on fetal. Convolutional Neural Network (CNN) is the method used by the authors in this study. Here will be classified 4 screening views of fetal heart using CNN with the pretrain model architecture VGG16, VGG19 and ResNet-50, where the main focus of the research is the average f1-score of the models produced during training and testing. CNN's classification yielded average f1-score of 100% for VGG16, and 99% for VGG19 and ResNet-50 for model training. After the trained model are obtained, it is used to classify the dataset outside the training data, the result is that the average f1-score is 99% for VGG16, 87% for VGG19, and 69% for ResNet50. VGG16 has the best results for classifying the used dataset.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002755	T40669	T406692021	Central Library (REFERENCES)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T406692021

Publisher

Inderalaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2021

Collation

xvii, 89 hlm. : ilus. ; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.607

Content Type

Text

Media Type

unmediated

Carrier Type

unspecified

Edition

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Subject(s)

Jaringan Komunikasi Komputer
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

Win

Other version/related

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