The up-to-date and accurate building footprint database plays a significant role in a large variety of applications. Recently, remote sensing images have provided an important data source for building footprint extrac...
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Navigating the world with visual impairments presents unique challenges, often limiting independence and safety. This research introduces SafeStride, a novel algorithm designed to empower visually impaired individuals...
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In the evolving landscape of business networks, the imperative to optimize power consumption has become paramount, particularly within the context of mixed wireless environments. This study introduces a novel approach...
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This study investigates a hybrid machine learning approach for the classification of cucumber leaf diseases, combining the strengths of pre-trained Convolutional Neural Networks (CNNs) and Support Vector Machines (SVM...
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Developing ultra-low-power devices requires low-power components, algorithms, and communication protocols. For environmental monitoring along the supply chain, products may travel a long way from the distributor to th...
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Fuel theft from Base Transceiver Station (BTS) generator sets (Gensets) is a prevalent issue that poses financial losses and operational disruptions for telecommunication companies. Traditional security measures have ...
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As long as a computer system is connected to the Internet, it is susceptible to attack as a victim. In computer networks, it becomes important to manage the network based on parameters such as network size and network...
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Alzheimer’s disease(AD)is a neurological disorder that predominantly affects the *** the coming years,it is expected to spread rapidly,with limited progress in diagnostic *** machine learning(ML)and artificial intell...
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Alzheimer’s disease(AD)is a neurological disorder that predominantly affects the *** the coming years,it is expected to spread rapidly,with limited progress in diagnostic *** machine learning(ML)and artificial intelligence(AI)algorithms have been employed to detect AD using single-modality ***,recent developments in ML have enabled the application of these methods to multiple data sources and input modalities for AD *** this study,we developed a framework that utilizes multimodal data(tabular data,magnetic resonance imaging(MRI)images,and genetic information)to classify *** part of the pre-processing phase,we generated a knowledge graph from the tabular data and MRI *** employed graph neural networks for knowledge graph creation,and region-based convolutional neural network approach for image-to-knowledge graph ***,we integrated various explainable AI(XAI)techniques to interpret and elucidate the prediction outcomes derived from multimodal ***-wise relevance propagation was used to explain the layer-wise outcomes in the MRI *** also incorporated submodular pick local interpretable model-agnostic explanations to interpret the decision-making process based on the tabular data *** expression values play a crucial role in AD *** used a graphical gene tree to identify genes associated with the ***,a dashboard was designed to display XAI outcomes,enabling experts and medical professionals to easily comprehend the predic-tion results.
The existing helmet detection algorithm is mainly based on a single-stage object detection algorithm, which has high detection speed and can achieve the requirement of real-time detection. Still, the accuracy of detec...
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In VANETs, the important and effective applications of vehicle localization include safety and communication applications. Thus, it is difficult to get very accurate localization in the dynamic and often very fluctuat...
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