This research discusses recent breakthroughs in brain tumour categorisation using MRI and a deep learning algorithm. Traditional brain tumour classifications cannot characterise complicated tumours similarly or use mu...
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Objective: Mobile robots leverage laser self-mixing interference for sensing in non-line-of-sight optical communications, allowing for a wide range of measures such as distance, velocity, and displacement, while also ...
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Virtualization in cloud computing enables efficient management of physical resources leading to affordable cloud services but has security vulnerabilities. The existing solutions are at a different level of privileges...
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Since the first instance was reported on January 30, 2020, India has seen a steady increase of Covid-19 cases, which has had a significant impact on stock market indices. This research examines the effects of the Covi...
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The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other h...
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The design of an antenna requires a careful selection of its parameters to retain the desired ***,this task is time-consuming when the traditional approaches are employed,which represents a significant *** the other hand,machine learning presents an effective solution to this challenge through a set of regression models that can robustly assist antenna designers to find out the best set of design parameters to achieve the intended *** this paper,we propose a novel approach for accurately predicting the bandwidth of metamaterial *** proposed approach is based on employing the recently emerged guided whale optimization algorithm using adaptive particle swarm optimization to optimize the parameters of the long-short-term memory(LSTM)deep *** optimized network is used to retrieve the metamaterial bandwidth given a set of *** addition,the superiority of the proposed approach is examined in terms of a comparison with the traditional multilayer perceptron(ML),Knearest neighbors(K-NN),and the basic LSTM in terms of several evaluation criteria such as root mean square error(RMSE),mean absolute error(MAE),and mean bias error(MBE).Experimental results show that the proposed approach could achieve RMSE of(0.003018),MAE of(0.001871),and MBE of(0.000205).These values are better than those of the other competing models.
Dermatoglyphics, the study of unique ridge patterns on fingertips, plays a crucial role in fingerprint-based identification. However, skin conditions such as psoriasis, eczema, and verruca vulgaris can distort these p...
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Privacy-preserving and secure data sharing are critical for medical image analysis while maintaining accuracy and minimizing computational overhead are also crucial. Applying existing deep neural networks (DNNs) to en...
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Camera calibration is of great significance. However, camera calibration still faces significant challenges. Target-based camera calibration depends on the accuracy of the calibration board and the extraction of corne...
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many organizations such as online organizations, hospitals, and universities use massive amounts of customer information and use Database systems to enter their data. Many services and benefits are provided by these o...
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To address the limitations of typical coil detection systems and enhance the performance of traditional magnetic field imaging (MFI) systems, we propose a MFI system that uses a 4×4 array of anisotropic magnetore...
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