Satellite image classification process involves grouping the image pixel values into
meaningful categories. Several satellite image classification methods and techniques are …

Classification of satellite images is the most important technique used in remote sensing for
the extraction and analysis of satellite information, which consists of grouping the values of …

High-velocity data streams present a challenge to deep learning-based computer vision
models due to the resources needed to retrain for new incremental data. This study presents …

Estimates of forest cover have important political, conservation, and funding implications, but
methods vary greatly. Haiti has often been cited as one of the most deforested countries in …

Satellite image classification is crucial in various applications such as urban planning,
environmental monitoring, and land use analysis. In this study, the authors present a …

[ES] La transformación del secano en regadío en el sector central de la Depresión del Ebro
ha representado un cambio espectacular en las condiciones de cultivo de un territorio de …

Diverse functional roles of multifunctional proteins arise from either their independent
functional domains or dual activities mediated through a single active site. Presence of …

Remotely sensed image segmentation and classification form a very important part of
remote sensing which involves geo-data processing and analysis. Artificial neural networks …

The aim of this study was to evaluate the efficiency of three support vector machine
algorithms, fuzzy decision trees and neural networks for mapping land vegetation map of …

In semi-arid environments like Zagros (western Iran), soil properties are influenced by
vegetation cover particularly tree species. This research addressed the effect of three oak …