Real-world data typically exhibits long-tailed class distribution and contains label noise. Previous long-tail learning ...
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Deep learning detects foodborne bacteria within three hours by eliminating debris misclassifications
Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in ...
Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in food by eliminating misclassifications of food debris that looks like bacteria ...
In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...
Abstract: This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.
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