Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
Abstract: A precise change detection in the multi-temporal optical images is considered as a crucial task. Although a variety of machine learning-based change detection algorithms have been proposed ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Morning Overview on MSN
Scientists build a ‘periodic table’ for AI models
Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...
Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
Abstract: Research and development of highly accurate falling detection systems (FDSs) for individuals with medical conditions or the elderly are crucial for mitigating the risks associated with falls ...
ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...
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: 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 ...
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