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161
Bootstrap-based Aggregations and their Stability in Feature Selection
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162
Development of a deep learning-based group contribution framework for targeted design of ionic liquids
Published 2024“…<p dir="ltr">In this article, we present a novel deep learning-based group contribution framework for the targeted design of ionic liquids (ILs). …”
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
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On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach
Published 2022“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”
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165
Machine Learning-based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction
Published 2024“…Respiration-correlated cone-beam computed tomography (4D-CBCT) is an X-ray-based imaging modality that uses reconstruction algorithms to produce time-varying volumetric images of moving anatomy over a cycle of respiratory motion. …”
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166
UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…Moreover, the study proposes a hybrid algorithm that combines UniBFS with two filter-based FS methods, ReliefF and Fisher, to identify pertinent features during the global search phase. …”
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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects
Published 2021“…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …”
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170
Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique
Published 2024“…The primary objective of this study is to estimate the CL index through an innovative approach that employs a hybrid, cluster-based, unsupervised learning technique seamlessly integrated with a 1D Convolutional Neural Network (CNN) architecture tailored for automated feature extraction, rather than conventional supervised algorithms, which facilitated in the acquisition of latent complex patterns without the need for manual categorization. …”
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171
Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments
Published 2025“…This paper presents a novel deep learning (DL)-based technique that leverages attention mechanisms to improve speech intelligibility through noise suppression. …”
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172
A collaborative filtering recommendation framework utilizing social networks
Published 2023“…The current study proposes a collaborative filtering recommendation framework that employs social networks to generate more precise and pertinent recommendations. The framework is based on a modified version of the user-based collaborative filtering algorithm, which computes user similarity based on their ratings and social connections. …”
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A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
Published 2025Get full text
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Practical Multiple Node Failure Recovery in Distributed Storage Systems
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Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework
Published 2022“…<div><p>Fog computing (FC) based sensor networks have emerged as a propitious archetype for next-generation wireless communication technology with caching, communication, and storage capacity services in the edge. …”
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A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies
Published 2024“…The fingerprinting and descriptors are two commonly approach for polymer featurization. In terms of algorithms, <u>neural networks</u> (NNs), random forest (RF), and gaussian process regression (GPR) are among the most extensively applied methods. …”