A rapid development of marine infrastructures can be observed along the global coasts.
Offshore wind farms, oil and gas platforms, artificial islands, aquaculture, and more, are …

Lithological mapping using dual-polarization synthetic aperture radar (SAR) data is limited
by the low classification accuracy. In this study, we extract ten parameters (backscatter …

Random Forest (RF) is a widely used machine learning algorithm for crop type mapping.
RF's variable importance aids in dimension reduction and identifying relevant multisource …

In image classification, the C4. 5, Adaboost, and Gradient Boosting algorithms need another
method to extract the image's features in the classification process. This research employs …

By introducing Indonesian batik motifs, we know that the island of Sumatra, especially
Bengkulu and Jambi provinces, has a distinctive batik called Basurek batik. This research …

This work considers a methodology for evaluating data augmentation effectiveness for target
classification in synthetic aperture radar (SAR) images. For the analysis, it is considered a …

This paper uses a signal separation method called Robust Principal Component Analysis
(RPCA) as a pre-processing technique to improve the classification of oil rigs in Synthetic …

This study investigates the application of Tensor Robust Principal Components analysis
(TRPCA) as a pre-processing tool in classifying oil rigs using synthetic aperture radar (SAR) …

In our study location, Merauke Regency, the easternmost city in Indonesia, the sago palm is
associated with different types of ecosystems and other non-sago vegetation. During the …

Feature extraction techniques play an essential role in classifying and recognizing targets in
synthetic aperture radar (SAR) images. This article proposes a hybrid feature extraction …