[HTML][HTML] Model aggregation techniques in federated learning: A comprehensive survey
Federated learning (FL) is a distributed machine learning (ML) approach that enables
models to be trained on client devices while ensuring the privacy of user data. Model …
models to be trained on client devices while ensuring the privacy of user data. Model …
A systematic review of disaster management systems: approaches, challenges, and future directions
Disaster management is a critical area that requires efficient methods and techniques to
address various challenges. This comprehensive assessment offers an in-depth overview of …
address various challenges. This comprehensive assessment offers an in-depth overview of …
Detection of autism spectrum disorder (ASD) in children and adults using machine learning
Autism spectrum disorder (ASD) presents a neurological and developmental disorder that
has an impact on the social and cognitive skills of children causing repetitive behaviours …
has an impact on the social and cognitive skills of children causing repetitive behaviours …
Reduction in data imbalance for client-side training in federated learning for the prediction of stock market prices
The approach of federated learning (FL) addresses significant challenges, including access
rights, privacy, security, and the availability of diverse data. However, edge devices produce …
rights, privacy, security, and the availability of diverse data. However, edge devices produce …
Beta Thalassemia Carriers detection empowered federated Learning
MS Farooq, HA Younas - arXiv preprint arXiv:2306.01818, 2023 - arxiv.org
Thalassemia is a group of inherited blood disorders that happen when hemoglobin, the
protein in red blood cells that carries oxygen, is not made enough. It is found all over the …
protein in red blood cells that carries oxygen, is not made enough. It is found all over the …
Artificial intelligence algorithms in flood prediction: a general overview
M Pandey - Geo-information for Disaster Monitoring and …, 2024 - Springer
This paper presents a comprehensive general overview of the extensive literature available
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …
in the field of application of artificial intelligence (AI) in flood prediction. The initial approach …
A distributed approach to meteorological predictions: addressing data imbalance in precipitation prediction models through federated learning and GANs
E Jafarigol, TB Trafalis - Computational Management Science, 2024 - Springer
The classification of weather data involves categorizing meteorological phenomena into
classes, thereby facilitating nuanced analyses and precise predictions for various sectors …
classes, thereby facilitating nuanced analyses and precise predictions for various sectors …
AI-empowered mobile edge computing: inducing balanced federated learning strategy over edge for balanced data and optimized computation cost
Abstract In Mobile Edge Computing, the framework of federated learning can enable
collaborative learning models across edge nodes, without necessitating the direct exchange …
collaborative learning models across edge nodes, without necessitating the direct exchange …
SSR-GAN: super resolution-based generative adversarial networks model for flood image enhancement
V Dubey, R Katarya - Signal, Image and Video Processing, 2024 - Springer
Floods, a common natural disaster, it affects more than half of all natural disasters, primarily
due to high floods, high tides, heavy rainfall, and human activity. Distinguishing between the …
due to high floods, high tides, heavy rainfall, and human activity. Distinguishing between the …
Enhancing Flood Resilience: Streamflow Forecasting and Inundation Modeling in Pakistan
Climatic changes have increased the frequency of natural disasters, and Pakistan, as a
developing nation, is facing severe challenges in coping with floods, which have …
developing nation, is facing severe challenges in coping with floods, which have …