Astronomers in Arizona turned to artificial intelligence to test out a new method of classifying meteors based on their physical properties and origin.
Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...
Machine learning (ML) is reshaping pipeline integrity management (PIM) from physics-based to data-driven paradigms. This ...
The 12-month engagement, titled "Enhancing Pathology through Quantum Computing,” is funded through Avanza UC 2025, the Internal Research and Creation Competition of UC Chile. To the collaborators’ ...
WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company") is a leading global Hologram Augmented Reality ("AR") Technology provider. A quantum deep convolutional neural network technology ...
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 ...
Abstract: Urban vegetation classification is challenging due to the heterogeneous nature of urban environments. Accurate mapping of urban vegetation, which plays a crucial role in regulating ...
Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...
The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Scientists say they have made a breakthrough after developing a quantum computing technique to run machine learning algorithms that outperform state-of-the-art classical computers. The researchers ...