Research on Input Schemes for Polarimetric SAR Classification Using Deep Learning

S Zhang, L Cui, Y Zhang, T Xia, Z Dong, W An - Remote Sensing, 2024 - mdpi.com
This study employs the reflection symmetry decomposition (RSD) method to extract
polarization scattering features from ground object images, aiming to determine the optimal …

Forest/Nonforest Segmentation Using Sentinel-1 and-2 Data Fusion in the Bajo Cauca Subregion in Colombia

A Guisao-Betancur, L Gómez Déniz… - Remote Sensing, 2023 - mdpi.com
Remote sensing technologies have been successfully used for deforestation monitoring,
and with the wide availability of satellite products from different platforms, forest monitoring …

Machine Learning-Based Rice Field Mapping in Kulon Progo using a Fusion of Multispectral and SAR Imageries

Y Khoirurrizqi, R Sasongko, NLE Utami, A Irbah… - Forum Geografi - journals.ums.ac.id
The land-conversion of rice fields can reduce rice production and negatively impact food
security. Consequently, monitoring is essential to prevent the loss of productive agricultural …

Evaluación de modelos de segmentación semántica para el monitoreo de deslizamiento de tierra utilizando imágenes satelitales

RM Yali Samaniego - tesis.pucp.edu.pe
En el ámbito del aprendizaje automático, un desafío persistente es la disponibilidad de
datos suficientes, especialmente en tareas de visión por computadora. Este desafío se …

[PDF][PDF] Assessment of Semantic Segmentation Models for Landslide Monitoring Using Satellite Imagery in Peruvian Andes

RYSP Fonseca, C Beltrán - research.latinxinai.org
In the domain of machine learning, one persistent challenge is the availability of ample data,
especially pertinent to computer vision. Moreover, this challenge is amplified within the …