Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...
Artificial Intelligence (AI) is revolutionizing the dynamics of technological advancement in the field of medical imaging, ...
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 ...
Background: Hip fractures are a major health concern in the older adults, severely impacting patients’ quality of life and straining healthcare systems. With China’s aging population, their incidence ...
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 ...
Abstract: In certain specialized domain scenarios, the collection of image data is rendered time-consuming and costly due to a variety of unique issues, making the assembly of extensive image datasets ...
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