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Kate Carlson, Barbara P. Buttenfield and Yi Qiang
Quantification of all types of uncertainty helps to establish reliability in any analysis. This research focuses on uncertainty in two attribute levels of wetland classification and creates visualization tools to guide analysis of spatial uncertainty pat...
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Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
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Marco Guerrieri, Giuseppe Parla, Masoud Khanmohamadi and Larysa Neduzha
Asphalt pavements are subject to regular inspection and maintenance activities over time. Many techniques have been suggested to evaluate pavement surface conditions, but most of these are either labour-intensive tasks or require costly instruments. This...
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Jean-Sébastien Dessureault, Félix Clément, Seydou Ba, François Meunier and Daniel Massicotte
The field of interior home design has witnessed a growing utilization of machine learning. However, the subjective nature of aesthetics poses a significant challenge due to its variability among individuals and cultures. This paper proposes an applied ma...
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Ivan G. Ivanov, Yordan Kumchev and Vincent James Hooper
Stroke is a major public health issue with significant economic consequences. This study aims to enhance stroke prediction by addressing imbalanced datasets and algorithmic bias. Our research focuses on accurately and precisely detecting stroke possibili...
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Çaglar Uyulan, David Mayor, Tony Steffert, Tim Watson and Duncan Banks
The field of signal processing using machine and deep learning algorithms has undergone significant growth in the last few years, with a wide scope of practical applications for electroencephalography (EEG). Transcutaneous electroacupuncture stimulation ...
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Quan Xu, Mengting Jin and Peng Guo
Timely and accurate information on crop planting structures is crucial for ensuring national food security and formulating economic policies. This study presents a method for high-precision crop classification using time-series UAV (unmanned aerial vehic...
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Jorge Bautista-Hernández and María Ángeles Martín-Prats
Cybersecurity plays a relevant role in the new digital age within the aerospace industry. Predictive algorithms are necessary to interconnect complex systems within the cyberspace. In this context, where security protocols do not apply, challenges to mai...
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Mohammed Abaker, Hatim Dafaalla, Taiseer Abdalla Elfadil Eisa, Heba Abdelgader, Ahmed Mohammed, Mohammed Burhanur, Aiman Hasabelrsoul, Mohammed Ibrahim Alfakey and Mohammed Abdelghader Morsi
In recent years, several strategies have been introduced to enhance early warning systems and lower the risk of rock-falls. In this regard, this paper introduces a deep learning- and IoT-based framework for rock-fall early warning, devoted to reducing ro...
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Ogbaje Andrew, Armando Apan, Dev Raj Paudyal and Kithsiri Perera
The accuracy of most SAR-based flood classification and segmentation derived from semi-automated algorithms is often limited due to complicated radar backscatter. However, deep learning techniques, now widely applied in image classifications, have demons...
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