Wetlands have long been recognized among the most critical ecosystems globally, yet their
numbers quickly diminish due to human activities and climate change. Thus, large-scale …

Many ecosystems, particularly wetlands, are significantly degraded or lost as a result of
climate change and anthropogenic activities. Simultaneously, developments in machine …

Accurate and efficient classification of wetlands, as one of the most valuable ecological
resources, using satellite remote sensing data is essential for effective environmental …

Convolutional Neural Networks (CNNs) have shown promising results in classifying
complex remote sensing scenery, particularly in the classification of wetlands. State-of-the …

Floods are devastating phenomena that occur almost all around the world and are
responsible for significant losses, in terms of both human lives and economic damages …

We propose a pioneering approach for gathering data on the forest canopy, one that merges
two cutting-edge technologies: ConvNext tiny and simple linear iterative clustering …

For the protection, restoration, and sustainable management of wetland ecosystems,
precision in extracting high-quality wetland land cover information is crucial. This study …

Advancements in deep learning are revolutionizing the classification of remote-sensing
images. Transformer-based architectures, utilizing self-attention mechanisms, have …

Dementia, an increasingly prevalent neurological disorder with a projected threefold rise
globally by 2050, necessitates early detection for effective management. The risk notably …

Classification of mushrooms are essential for preventing even life-threatening
consequences of accidentally eating wild mushrooms. In this study, a dataset including 114 …