Abstract: Spectral clustering algorithms rely on graphs where edges are defined based on the similarity between the vertices (data points). The effectiveness and fairness of spectral clustering depend ...

Python API for reading WINISI .cal files (spectral data files used in NIR applications). The feature should enable users to extract spectral data, sample information, and metadata from .cal files. It ...

WEST LAFAYETTE, Ind. — Professionals in agriculture, defense and security, environmental monitoring, food quality analysis, industrial quality control, and medical diagnostics could benefit from a ...

Abstract: Traditional spectral clustering methods struggle with scalability and robustness in large datasets due to their reliance on similarity matrices and EigenValue Decomposition. We introduce two ...

CACI International has secured a $143 million delivery order from the U.S. Navy to provide spectral enabling kits designed to deliver electronic warfighting capabilities to the military branch’s ...

Spectral AI’s Deepview System has outperformed burn physicians in identifying non-healing tissue, the company said Monday. Deepview achieved 86.6% sensitivity when identifying non-healing tissue at an ...

Researchers have developed a new AI algorithm, called Torque Clustering, that is much closer to natural intelligence than current methods. It significantly improves how AI systems learn and uncover ...