Nowadays, using chatbots in the corporate and technology worlds is necessary. The recent development of chatbots like ChatGPT has raised various issues for technological titans and academic researchers, particularly w...
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The Coronavirus Disease (COVID)-19 pandemic is fast changing our way of life and interfering with international travel and trade. The norm now is to wear a protective facemask. Many public service providers may soon d...
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Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D *** algorithm for restoring the original 3D hyperspectral images(HSIs)from compressive measurements is pivo...
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Spectral compressive imaging has emerged as a powerful technique to collect the 3D spectral information as 2D *** algorithm for restoring the original 3D hyperspectral images(HSIs)from compressive measurements is pivotal in the imaging *** approaches painstakingly designed networks to directly map compressive measurements to HSIs,resulting in the lack of interpretability without exploiting the imaging *** some recent works have introduced the deep unfolding framework for explainable reconstruction,the performance of these methods is still limited by the weak information transmission between iterative *** this paper,we propose a Memory-Augmented deep Unfolding Network,termed MAUN,for explainable and accurate HSI ***,MAUN implements a novel CNN scheme to facilitate a better extrapolation step of the fast iterative shrinkage-thresholding algorithm,introducing an extra momentum incorporation step for each iteration to alleviate the information ***,to exploit the high correlation of intermediate images from neighboring iterations,we customize a cross-stage transformer(CSFormer)as the deep denoiser to simultaneously capture self-similarity from both in-stage and cross-stage features,which is the first attempt to model the long-distance dependencies between iteration *** experiments demonstrate that the proposed MAUN is superior to other state-of-the-art methods both visually and *** code is publicly available at https://***/HuQ1an/MAUN.
The proposed system's objective is to improve the performance of diagnosing liver diseases through machine learning by using the Random Forest algorithm. Such systems accommodate a detailed database that comprises...
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Current study aims to numerically investigate the bi-directional flow of nanofluids in the presence of Cattaneo–Christov double diffusion for two heat sources, namely, prescribed surface temperature (PST) along with ...
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The Online social networks (OSN) popularity and use increases recently. Due to their immense popularity across a wide range of users, hackers use this platform to spread fake news, promotion of specific ideas and prod...
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The recognition of secure data transmission in a cloud platform requires the integrity of sensitive information with higher confidentiality. This is obtained using the aid of deep learning techniques. The robustness o...
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YouTube's video recommendation method stands as a pinnacle in the realm of content discovery in enhancing user engagement on the *** User-Based Collaborative Filtering recommendation method relies on a robust foun...
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Deep learning(DL) systems exhibit multiple behavioral characteristics such as correctness, robustness, and fairness. Ensuring that these behavioral characteristics function properly is crucial for maintaining the accu...
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Next-generation Internet of Things (IoT) is progressing rapidly due to the introduction of beyond 5G (B5G) and the approaching arrival of 6G, which have improved the dependability, productivity, and profitability of b...
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