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Blood Glucose Regulation Modelling and Intelligent Control
Published 2024Get full text
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MSD-NAS: multi-scale dense neural architecture search for real-time pedestrian lane detection
Published 2023“…<p dir="ltr">Accurate detection of pedestrian lanes is a crucial criterion for vision-impaired people to navigate freely and safely. The current deep learning methods have achieved reasonable accuracy at this task. …”
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Artificial Intelligence for Skin Cancer Detection: Scoping Review
Published 2021“…Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.…”
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A hybrid graph representation for recursive backtracking algorithms
Published 2017“…The performance of these algorithms often suffers from the increasing number of graph modifications, such as deletions, that reduce the problem instance and have to be “taken back” frequently during the search process. …”
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DAP: A dataset-agnostic predictor of neural network performance
Published 2024“…This task often must be repeated many times, especially when developing a new deep learning algorithm or performing a neural architecture search. …”
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A Comprehensive Review of AI’s Current Impact and Future Prospects in Cybersecurity
Published 2025“…We examine cutting-edge AI methodologies and principal models across many domains, including machine learning algorithms, deep learning architectures, natural language processing techniques, and anomaly detection algorithms, emphasizing their distinct contributions to enhancing security. …”
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Distributed DRL-Based Downlink Power Allocation for Hybrid RF/VLC Networks
Published 2021“…We implement a simulation environment to benchmark the proposed distributed DRL-based method against other methods such as Q-Learning (QL) and Deep Q-Networks (DQN), and centralized heuristic power allocation algorithms. …”
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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DRL-Based UAV Path Planning for Coverage Hole Avoidance: Energy Consumption and Outage Time Minimization Trade-Offs
Published 2025“…As such, in addition to avoiding coverage holes, we should also make the outage time as small as possible. By deploying a deep reinforcement learning algorithm, we find optimal UAV paths based on the two families of trajectories: spiral and oval curves, to tackle different design considerations and constraints, in terms of QoS, energy consumption and coverage hole avoidance. …”
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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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