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This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.
This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.
This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.
This technology introduces an advanced machine learning approach for enhancing chemical imaging by correlating data from two mass spectrometry imaging (MSI) techniques.
Ionic liquids comprising quaternary ammonium and phosphonium cations have been developed as eco-friendly lubricant additives. These additives are tailored for use in environmentally acceptable lubricants (EALs) like polyalkylene glycols, vegetable oils, and synthetic esters.
A high-strength, heat-resistant Al-Ce-Ni alloy optimized for additive manufacturing in industrial applications.
The need for accurate temperature measurement in critical environments such as nuclear reactors is paramount for safety and efficiency.
High-performance cerium-based permanent magnet materials have been developed to reduce reliance on scarce rare-earth elements.
Aromas play a significant role in the quality and safety of food, beverages, and even manufactured products. The ability to detect and interpret these aromas accurately can enhance product safety and consumer satisfaction.