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201
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
Published 2022“…<p dir="ltr">Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. …”
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202
Human Action Recognition: A Taxonomy-Based Survey, Updates, and Opportunities
Published 2023“…One of the most challenging issues for computer vision is the automatic and precise identification of human activities. A significant increase in feature learning-based representations for action recognition has emerged in recent years, due to the widespread use of deep learning-based features. …”
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203
Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction
Published 2020“…This paper presents an efficient non-intrusive load monitoring framework that consists of the following main components: (i) a novel fusion of multiple time-domain features is proposed to extract appliance fingerprints; (ii) a dimensionality reduction scheme is introduced to be applied to the fused time-domain features, which relies on fuzzy-neighbors preserving analysis based QR-decomposition. …”
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204
Evaluating machine learning technologies for food computing from a data set perspective
Published 2023“…Food computing benefits from technologies based on modern machine learning techniques, including deep learning, deep convolutional neural networks, and transfer learning. …”
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205
A systematic review and meta-analysis on the impact of early vs. delayed pharmacological thromboprophylaxis in patients with traumatic brain injury
Published 2024“…Early PTP was categorized based on the timing of administration: 1) within 24 h, 2) within 48 h, and 3) within 72 h of hospital admission. …”
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206
A New Flow-Based Approach for Enhancing Botnet Detection Efficiency Using Convolutional Neural Networks and Long Short-Term Memory
Published 2025“…<p dir="ltr">Despite the growing research and development of botnet detection tools, an ever-increasing spread of botnets and their victims is being witnessed. …”
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Food fraud detection using explainable artificial intelligence
Published 2023“…<div><p>Recently, the global food supply chain has become increasingly complex, and its scalability has grown. …”
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Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation
Published 2024“…<p dir="ltr">Effective modeling of patient representation from electronic health records (EHRs) is increasingly becoming a vital research topic. Yet, modeling the non-stationarity in EHR data has received less attention. …”
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TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images
Published 2024“…However, it is difficult to identify TB from CXR images in the early stage, which leads to time-consuming and expensive treatments. Moreover, due to the increase of drug-resistant tuberculosis, the disease becomes more challenging in recent years. …”
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213
Towards electric digital twin grid: Technology and framework review
Published 2023“…Electric Digital Twin grid can perform online analysis of the grid in real-time and integrates all the past and present data and express the current grid status to the producers and consumers and also predicts the future grid status. …”
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Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…These are considered to be an increasing trend, and it will be a major challenge to reduce risk, especially in the future. …”
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216
Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review
Published 2023“…It provides key insights into how vision transformers complemented the performance of AI and deep learning methods for lung cancer. Furthermore, the review also identifies the datasets that contributed to advancing the field.…”
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Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS
Published 2025“…To improve our results and increase our dataset, we use data augmentation with a deep convolutional generative adversarial network (DCGAN). …”
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Published 2019“…., its generation, propagation and mitigation, in order to increase operational efficiency and improve livability within smart cities. …”