Abstract: Satellite image classification is vital for applications like environmental monitoring, urban planning, and resource management. Manual methods are time-consuming and error-prone, ...
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...
Abstract: Aiming at the challenges of high intra-class disparity and low inter-class disparity in fine-grained image classification, a multi-branch fine-grained image classification method based on ...
An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...
A comprehensive Python library for processing French IGN LiDAR HD data into machine learning-ready datasets. Features include GPU acceleration, rich geometric features, RGB/NIR augmentation, and ...
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
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