Image of SEGMENTASI AKAR PADA CITRA TANAH DENGAN MENGIMPLEMENTASIKAN METODE ENSEMBLE LEARNING MENGGUNAKAN TEKNIK WEIGHTED AVERAGE PADA ARSITEKTUR U-NET DAN DENSENET

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SEGMENTASI AKAR PADA CITRA TANAH DENGAN MENGIMPLEMENTASIKAN METODE ENSEMBLE LEARNING MENGGUNAKAN TEKNIK WEIGHTED AVERAGE PADA ARSITEKTUR U-NET DAN DENSENET

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The purpose of this study was to obtain an accurate segmentation model in predicting roots using a soil image dataset. This research implements ensemble learning with a weighted average technique on U-Net and DenseNet architectures for root segmentation in soil images. The research stages are data description, data pre-processing, training, testing, and performance evaluation as well as making conclusions. In this study, the results obtained from the performance evaluation of a single architecture, namely accuracy, sensitivity, specificity, precision, F1-Score, and IoU obtained from the U-Net architecture respectively, are 99.69% in this study, 75.75%, 99.76%, 66.63%, 70.87%, and 54.38%. While the results obtained from DenseNet architecture are 99.52%, 71.33%, 99.72%, 66.68%, 67.29%, and 50.71%. The results of the implementation of ensemble learning on U-Net and DenseNet architectures are 99.75%, 92.82%, 99.87%, 92.68%, 92.75%, and 86.49%, respectively. Based on the results obtained, it can be concluded that the implementation of ensemble learning on U-Net and DenseNet architectures can segment the roots of the soil image very well. The implementation of ensemble learning can also improve architectural performance and overcome the problem of overfitting in single architecture segmentation.

Availability
Inventory Code Barcode Call Number Location Status
2207005183T84725T847252022Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T847252022
Publisher
Inderalaya : Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Sriwijaya.,
Collation
xii, 70 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
519.07
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Matematika Terapan
Jurusan Matematika
Specific Detail Info
-
Statement of Responsibility
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