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learning algorithm » learning algorithms (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
level learning » deep learning (Expand Search)
element » elements (Expand Search)
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Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review
Published 2023“…Most of the included articles used data sets with a size of <1000 samples (11/30, 37%). Deep learning models were the most prominent branch of AI used for pancreatic cancer diagnosis in the studies, and the convolutional neural network was the most used algorithm (18/30, 60%). …”
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Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers
Published 2023“…<p dir="ltr">This article proposes a digital twin (DT)-based diagnosis and fault-tolerant control for T-type three-level rectifiers. To develop the DT, a dense deep neural network (DNN) machine learning approach is used. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”
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Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012)
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masterThesis -
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Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection
Published 2022“…We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. …”
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XBeGene: Scalable XML Documents Generator by Example Based on Real Data
Published 2012“…Inspired by the query-by-example paradigm in information retrieval, Our generator system i)allows the user to provide her own sample XML documents as input, ii) analyzes the structure, occurrence frequencies, and content distributions for each XML element in the user input documents, and iii) produces synthetic XML documents which closely concur, in both structural and content features, to the user's input data. …”
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Identification of phantom movements with an ensemble learning approach
Published 2022“…The aim of the current study is to classify and recognize the phantom movements in four different amputation levels of the upper and lower extremities. In the current study, we utilized ensemble learning algorithms for the recognition and classification of phantom movements of the different amputation levels of the upper and lower extremity. …”
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling
Published 2022“…In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. …”
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masterThesis -
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A Data-Driven Decision-Making Framework for Fleet Management in the Government Sector of Dubai
Published 2024“…The proposed framework comprises key elements: Important Decisions derived from interviews with transportation leaders, Knowledge Management enhanced by AI algorithms, Data Mining/Analysis utilizing historical data, the Fleet Management System employing Oracle ERP, and a Data-Driven Decision Support Framework that leans towards the extended framework approach. …”
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Brain Source Localization in the Presence of Leadfield Perturbations
Published 2015Get full text
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Reinforcement Learning-Based School Energy Management System
Published 2020“…In recent years, the Deep Reinforcement Learning algorithm, applying neural networks for function approximation, shows promising results in handling such complex problems. …”
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Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…These discriminative motifs can be further studied to understand their role both at the evolutionary and disease levels.…”
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masterThesis -
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Learning-Based Spectrum Sensing and Access for Cognitive Radio Systems
Published 2015Get full text
doctoralThesis -
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2020“…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. …”
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An efficient approach for textual data classification using deep learning
Published 2022“…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”