Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
Abstract: Intelligent transportation systems are increasingly reliant on precise and efficient vehicle classification to support traffic management, safety applications, and infrastructure planning.
A pioneering study reveals how archaeologists' satellite tools can be repurposed to tackle climate change. By using AI and satellite LiDAR imagery from NASA and ESA, researchers have found a faster, ...
ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...
Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
@IvanNardi As per our initial discussion: Is your feature request related to a problem? Please describe. Detecting malware and covert communications within encrypted traffic, especially when ...
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