Search by :

ALL Author Subject ISBN/ISSN Advanced Search

Last search:

Image of KLASIFIKASI PENYAKIT MATA PADA CITRA RETINA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DAN GRAD-CAM

Skripsi

KLASIFIKASI PENYAKIT MATA PADA CITRA RETINA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DAN GRAD-CAM

Muhammad, Damar Fadhil - Personal Name;

Penilaian

0,0

dari 5

Eye diseases can be detected by examining the retina of the eye. Therefore, this research develops a system using Convolutional Neural Network (CNN) and Gradient-Weighted Class Activation Map (Grad-CAM) methods that can help diagnose eye diseases based on retinal images. The CNN method is used to classify whether there is a disease or not, so that the system can diagnose the disease suffered by the patient. However, this method has the disadvantage that it cannot display a visual explanation of the classification results, to cover this deficiency this method is combined with Grad-CAM. Grad-CAM can provide a visual explanation of the classification results in the form of a heatmap, so that users of this system can understand the reasons behind the CNN method classifying to a certain class. This research compares the architecture of InceptionV3, MobileNetV2, VGG-16, and various configurations on epoch, learning rate, and batch size in building the best CNN model. The dataset used in this study consists of 4 classes and totals 4217 data. The test results in this study produced the best CNN model using InceptionV3 architecture, epoch = 50, learning rate = 0,0001, and batch size = 8 with an accuracy value of 96,3%.

Availability

Inventory Code	Barcode	Call Number	Location	Status
2407004336	T151006	T1510062024	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title: -
Call Number: T1510062024
Publisher: Indralaya : Prodi Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2024
Collation: xii, 117 hlm.; ilus.; 29 cm
Language: Indonesia
ISBN/ISSN: -
Classification: 006.370 7
Content Type: Text
Media Type: unmediated
Carrier Type: -
Edition: -
Subject(s): penyakit mata
Prodi Teknik Informatika
Specific Detail Info: -
Statement of Responsibility: KA

Other version/related

Title	Edition	Language
METODE ENSEMBLE LEARNING MENGGUNAKAN TEKNIK WEIGHTED VOTING PADA HASIL DENSENET, EFFICIENTNET DAN VISION TRANSFORMER DALAM KLASIFIKASI PENYAKIT MATA		id
PENERAPAN DEEP LEARNING UNTUK KLASIFIKASI PENYAKIT MATA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN): ARSITEKTUR DENSENET 121 DAN XCEPTION		id
IMPLEMENTASI DEEP LEARNING UNTUK KLASIFIKASI PENYAKIT MATA DENGAN STUDI PERBANDINGAN ARSITEKTUR INCEPTIONV3 DAN VGG-16 PADA CONVOLUTIONAL NEURAL NETWORK (CNN)		id

File Attachment

KLASIFIKASI PENYAKIT MATA PADA CITRA RETINA MENGGUNAKAN CONVOLUTIONAL NEURAL NETWORK DAN GRAD-CAM

Comments

You must be logged in to post a comment