Researchers from Hebei University and Hebei University of Engineering have developed a hyperspectral imaging method combined with data fusion and machine learning to accurately and non-destructively assess walnut quality and classify storage periods.
A new study demonstrates that paper bagging significantly enhances Fuji apple quality and appearance. Hyperspectral imaging combined with machine learning offers a powerful, non-destructive method for evaluating fruit grown under different cultivation conditions.
In this study, the feasibility of the rapid discrimination of three different geographical origins of purple sweet potato with a hyperspectral imaging (HSI) system was examined.
Hyperspectral imaging was recently used to characterize chicken breast affected by myopathies, which can affect their texture and quality.
A recent study combines hyperspectral imaging (HSI) technology with chemometrics to deliver improved quality control of black garlic.
A recent review article looks at how wetland ecosystems are being monitored using remote sensing technologies and imaging spectroscopy to better manage them.
A Monday morning session at the Eastern Analytical Symposium in Plainsboro, New Jersey, highlighted hyperspectral and biological imaging techniques.
During the conference in Raleigh, North Carolina, experts from universities around the world spoke about their research using Raman, infrared spectroscopy, and more for biomedical imaging.
Webinar Date/Time: Thursday, September 12th, 2024 English Session: 10:00 AM BST | 11:00 AM CEST French Session: 10:00 AM BST | 11:00 AM CEST
A recent study introduced a new scanning X-ray fluorescence (MA-XRF) scanner that improves analysis of cultural heritage artifacts.
Forensic scientists have made significant strides in bloodstain identification, leveraging advanced hyperspectral imaging and machine learning to distinguish between human and animal bloodstains with remarkable accuracy.
Hokkaido University scientists are investigating a more sustainable approach for detecting arsenic in minerals.
Webinar Date/Time: Wednesday, June 26th, 2024 at 8am PDT | 11am EDT | 4pm BST | 5pm CEST
Korean scientists recently tested a new light detection and ranging (LiDAR)-based system for improving autonomous recognition systems.
Here, we dive into hyperspectral imaging (HSI) and highlight a few recent studies using HSI in various applications.
Here are the top five articles that the editors of Spectroscopy published this week.
Scientists from Nanjing Forestry University recently used a portable hyperspectral imager to help detect maturity stages in Camellia oleifera fruits.
Webinar Date/Time: Thu, May 23, 2024 1:00 PM EDT
Rigaku Analytical Devices has been awarded a third year of funding for a TSA contract dedicated to creating better-optimized screening equipment.
A PhD student in the Department of Bioengineering at the University of Pennsylvania has won the 2024 Physics of Medical Imaging Student Paper Award, which is given out annually by the International Society for Optics and Photonics (SPIE), at the Medical Imaging Symposium in San Diego, California.
Ana Doblas of the University of Massachusetts Dartmouth presented her team’s findings on how models based on deep learning (DL) can enhance different microscopy imaging infrastructures.
A team of scientists have used airborne lidar mapping to study Mayan architecture, seeing how certain buildings’ construction can hint at the social status of their inhabitants.
Utilizing a low-altitude unmanned aerial vehicle (UAV), a hyperspectral remote-sensing system can identify key grass species indicating grassland degradation, developing an ASI index and classification rules and leveraging spectral differences and plant senescence reflectance to effectively monitor and evaluate grassland conditions and degradation.
This tutorial illustrates spectroscopic imaging principles, applications, advantages, and limitations for UV-vis, FL, NIR, IR, THz, Raman, XRF, ICP-MS, and LIBS techniques. It provides a guide for understanding spectroscopic imaging for diverse sample types and applications.
This study explores the enhanced performance of modified alternating least squares (MALS) over alternating least squares (ALS) in analyzing infrared and Raman image spectral data, highlighting the stability and computational efficiency of MALS.
