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Deep learning framework for automatic detection and classification of sleep apnea severity from polysomnography signals
Sleep apnea (SA) is a sleep-related breathing disorder characterized by breathing pauses during sleep. A person’s sleep schedule is significantly...
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Advanced RIME architecture for global optimization and feature selection
The article introduces an innovative approach to global optimization and feature selection (FS) using the RIME algorithm, inspired by RIME-ice...
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Kids Learning Optimizer: social evolution and cognitive learning-based optimization algorithm
This paper proposes a novel social cognitive learning-based metaheuristic called kids Learning Optimizer (KLO), inspired by the early social learning...
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Feature reduction for hepatocellular carcinoma prediction using machine learning algorithms
Hepatocellular carcinoma (HCC) is a highly prevalent form of liver cancer that necessitates accurate prediction models for early diagnosis and...
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Adaptive neuro-fuzzy sliding mode control of the human upper limb during manual wheelchair propulsion: estimation of continuous joint movements using synergy-based extended Kalman filter
Wheelchair upper limb exoskeletons can present a revolutionary approach to aid individuals with neuromuscular disorders in their daily tasks, which...
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Data oversampling and imbalanced datasets: an investigation of performance for machine learning and feature engineering
The classification of imbalanced datasets is a prominent task in text mining and machine learning. The number of samples in each class is not...
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MOAAA/D: a decomposition-based novel algorithm and a structural design application
When real-world engineering challenges are examined adequately, it becomes clear that multi-objective need to be optimized. Many engineering problems...
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Advancing machine learning with OCR2SEQ: an innovative approach to multi-modal data augmentation
OCR2SEQ represents an innovative advancement in Optical Character Recognition (OCR) technology, leveraging a multi-modal generative augmentation...
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Correlation-based outlier detection for ships’ in-service datasets
With the advent of big data, it has become increasingly difficult to obtain high-quality data. Solutions are required to remove undesired outlier...
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A systematic data characteristic understanding framework towards physical-sensor big data challenges
Big data present new opportunities for modern society while posing challenges for data scientists. Recent advancements in sensor networks and the...
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Gene selection based on recursive spider wasp optimizer guided by marine predators algorithm
Detecting tumors using gene analysis in microarray data is a critical area of research in artificial intelligence and bioinformatics. However, due to...
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Data pipeline approaches in serverless computing: a taxonomy, review, and research trends
Serverless computing has gained significant popularity due to its scalability, cost-effectiveness, and ease of deployment. With the exponential...
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On data efficiency of univariate time series anomaly detection models
In machine learning (ML) problems, it is widely believed that more training samples lead to improved predictive accuracy but incur higher...
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Hypoxia within tumor microenvironment characterizes distinct genomic patterns and aids molecular subty** for guiding individualized immunotherapy
Assessing the hypoxic status within the tumor microenvironment (TME) is crucial for its significant clinical relevance in evaluating drug resistance...
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EnParaNet: a novel deep learning architecture for faster prediction using low-computational resource devices
The deployment of deep learning architectures on low-computational resource devices is challenging due to their high number of parameters and...
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DATE: a video dataset and benchmark for dynamic hand gesture recognition
This paper proposes a new Dynamic hAnd gesTurE (DATE) dataset for dynamic hand gestures. The DATE dataset contains 13,500 videos of 22 different...
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A self-attention-based deep architecture for online handwriting recognition
The self-attention mechanism has been the most frequent and efficient way for processing and learning sequences in numerous domains of artificial...
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Noise reduction deep CNN-based retinal fundus image enhancement using recursive histogram
Retinal imaging often falls short in image quality due to limitations in imaging conditions. Issues such as low contrast and inadequate brightness...
