Deep learning (DL) algorithms have seen a massive rise in popularity for remote-sensing
image analysis over the past few years. In this study, the major DL concepts pertinent to …

Big Data and machine learning (ML) technologies have the potential to impact many facets
of environment and water management (EWM). Big Data are information assets …

Object detection in remote sensing images (RSIs) requires the locating and classifying of
objects of interest, which is a hot topic in RSI analysis research. With the development of …

Tree-crown and height are primary tree measurements in forest inventory. Convolutional
neural networks (CNNs) are a class of neural networks, which can be used in forest …

This paper aims to assist in the prevention of Chronic Kidney Disease (CKD) by utilizing
machine learning techniques to diagnose CKD at an early stage. Kidney diseases are …

Although the orientation and scale properties of the objects in remote sensing images have
been widely considered in the modern deep learning-based object detection methods, the …

In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by
investigating aggregated classes. The increase in data with a very high spatial resolution …

Advancements in the development of deep learning and computer vision-based approaches
have the potential to provide managers and engineers with the ability to improve the safety …

Object detection from aerial and satellite remote sensing images has been an active
research topic over the past decade. Thanks to the increase in computational resources and …

Object detection (OD) is an important task of computer vision and has been widely used in
many fields, including remote sensing (RS). However, the complex scenes, large-scale …