Browse Items (4 total)
Sort by:
Land Cover Segmentation of Multispectral Images Using U-Net and DeeplabV3+ Architecture
The application of Deep Learning has now extended to various fields, including land cover classification. Land cover classification is highly beneficial for urban planning. However, the current methods heavily rely on statistical-based applications,…
Encoder-Decoder with Atrous Spatial Pyramid Pooling for Left Ventricle Segmentation in Echocardiography
Assessment of cardiac function using echocardiography is an essential and widely used method. Assessment by manually labeling the left ventricle area can generally be time-consuming, error-prone, and has interobserver variability. Thus, automatic…
TELKOMNIKA Telecommunication, Computing, Electronics and Control
UNet-VGG16 with transfer learning for MRI-based brain tumor segmentation
A brain tumor is one of a deadly disease that needs high accuracy in its
medical surgery. Brain tumor detection can be done through magnetic
resonance imaging (MRI). Image segmentation for the MRI brain tumor aims to separate the tumor area (as the…
medical surgery. Brain tumor detection can be done through magnetic
resonance imaging (MRI). Image segmentation for the MRI brain tumor aims to separate the tumor area (as the…
Journal of ICT Research and Applications ITB Bandung Vol. 15 No. 1 2021
Unsupervised Detection of Anomalous Sound for Machine Condition Monitoring using Fully Connected U-Net
Abstract. Anomaly detection in the sound from machines is an important task in machine monitoring. An autoencoder architecture based on the reconstruction error using a log-Mel spectrogram feature is a conventional approach for this domain. However,…