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learning algorithm » learning algorithms (Expand Search)
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Practical Multiple Node Failure Recovery in Distributed Storage Systems
Published 2016“…The fractional repetition (FR) code is a class of regenerating codes that consists of a concatenation of an outer maximum distance separable (MDS) code and an inner fractional repetition code that splits the data into several blocks and stores multiple replicas of each on different nodes in the system. …”
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conferenceObject -
83
Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images
Published 2023“…Considering these shortcomings, computational methods especially machine learning and deep learning algorithms are leveraged as an alternative to accelerate the accurate detection of CT scans as cancerous, and non-cancerous. …”
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A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Published 2022“…Every communication body wants to secure their data while communicating over the Internet. The internet has various benefits but the main demerit is the privacy and security and the transmission of data over insecure network or channel may happen. …”
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86
Artificial Intelligence for Assessing the Correlation Between Sleep Apnoea and Comorbidities
Published 2022Get full text
doctoralThesis -
87
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
Published 2025“…The proposed DRL controllers are benchmarked against model-based controllers, i.e., linear quadratic regulator with the sequential quadratic programming (LSQP) and sliding mode control with SQP (SSQP). …”
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The automation of the development of classification models and improvement of model quality using feature engineering techniques
Published 2023“…<p>Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. …”
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A heuristics for HTTP traffic identification in measuring user dissimilarity
Published 2020“…The application of these research findings finds relevance in user identification for insider investigation, e-commerce, and e-learning system as well as in network planning and management. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
Published 2023“…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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Detecting and Predicting Archaeological Sites Using Remote Sensing and Machine Learning—Application to the Saruq Al-Hadid Site, Dubai, UAE
Published 2023“…The modelling and prediction accuracies are expected to improve with the insertion of a neural network and backpropagation algorithms based on the performed cluster groups following more recent field surveys. …”
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Rate Adaptation in Dynamic Adaptive Video Streaming Over HTTP
Published 2021Get full text
doctoralThesis -
96
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97
Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model
Published 2024“…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”
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Integrated whole transcriptome and small RNA analysis revealed multiple regulatory networks in colorectal cancer
Published 2021“…Additionally, potential interaction between differentially expressed lncRNAs such as H19, SNHG5, and GATA2-AS1 with multiple miRNAs has been revealed. Taken together, our data provides thorough analysis of dysregulated protein-coding and non-coding RNAs in CRC highlighting numerous associations and regulatory networks thus providing better understanding of CRC.…”
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A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns
Published 2023“…This study proposes a hybrid scheme where two machine-learning (ML) models are coupled in a series to predict the PG value without any conclusive FP information. …”
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