WSN has been exhilarated in many application areas such as military, medical, envi-ronment, etc. Due to the rapid increase in applications, it causes proportionality to security threats because of its wireless communi...
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In this paper, a BCI-based machine learning method is proposed to predict the attention lapse of the driver. An EEG headset is used to capture brain activity from different regions of the human brain. The data is furt...
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Developing effective strategies to address significant variations in segmented iris image quality is crucial for accurate iris recognition from remotely acquired facial or eye images. These variations are closely link...
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In this digital era, users frequently share their thoughts, preferences, and ideas through social media, which reflect their Basic Human Values. Basic Human Values (aka values) are the fundamental aspects of human beh...
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In image registration, traditional optimization techniques are incapable of detecting the optimum value of geometric transformation parameters. To resolve this issue, a novel scheme of monomodal (isomodal) biomedical ...
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The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident preventi...
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The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic *** these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle *** paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly ***-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV *** examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.
In this ambitious agricultural project, cutting-edge technologies such as Machine Learning (ML) and Deep Learning (DL) are harnessed to revolutionize farming practices in India. The primary focus lies in automating vi...
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Segment Routing is a source routing paradigm that simplifies packet forwarding and management across networks. Two major challenges of segment routing are the limitation of header stack size and the size of the Forwar...
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The electrocardiogram is a vital piece of information about a person's health that provides measurements of changes in the cardiovascular system. When using complex software modules to diagnose diseases, the clini...
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This study presents a comprehensive intervention approach designed to address dyscalculia in early education. The strategy employs a comprehensive approach that incorporates colour identification, numerical enumeratio...
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