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Hyperspectral Imaging

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Analyzing 3D hyperspectral TOF-SIMS depth profile data using self-organizing map-relational perspective mapping.

Biointerphases
The advantages of applying multivariate analysis to mass spectrometry imaging (MSI) data have been thoroughly demonstrated in recent decades. The identification and visualization of complex relationships between pixels in a hyperspectral data set can...

Nondestructive Detection for Egg Freshness Based on Hyperspectral Scattering Image Combined with Ensemble Learning.

Sensors (Basel, Switzerland)
Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy, and explain it...

Understanding mass spectrometry images: complexity to clarity with machine learning.

Biopolymers
The application of artificial intelligence and machine learning to hyperspectral mass spectrometry imaging (MSI) data has received considerable attention over recent years. Various methodologies have shown great promise in their ability to handle the...

Adoption of Machine Learning in Intelligent Terrain Classification of Hyperspectral Remote Sensing Images.

Computational intelligence and neuroscience
To overcome the difficulty of automating and intelligently classifying the ground features in remote-sensing hyperspectral images, machine learning methods are gradually introduced into the process of remote-sensing imaging. First, the PaviaU, Botswa...

Detection and identification of Cannabis sativa L. using near infrared hyperspectral imaging and machine learning methods. A feasibility study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Remote identification of illegal plantations of Cannabis sativa Linnaeus is an important task for the Brazilian Federal Police. The current analytical methodology is expensive and strongly dependent on the expertise of the forensic investigator. A fa...

Unified Classification of Bacterial Colonies on Different Agar Media Based on Hyperspectral Imaging and Machine Learning.

Molecules (Basel, Switzerland)
A universal method by considering different types of culture media can enable convenient classification of bacterial species. The study combined hyperspectral technology and versatile chemometric algorithms to achieve the rapid and non-destructive cl...

Hyperspectral imaging for accurate determination of rice variety using a deep learning network with multi-feature fusion.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The phenomena of rice adulteration and shoddy rice arise continuously in high-quality rice and reduce the interests of producers, consumers and traders. Hyperspectral imaging (HSI) was conducted to determine rice variety using a deep learning network...

Hyperspectral imaging combined with machine learning as a tool to obtain high-throughput plant salt-stress phenotyping.

The Plant journal : for cell and molecular biology
The rapid selection of salinity-tolerant crops to increase food production in salinized lands is important for sustainable agriculture. Recently, high-throughput plant phenotyping technologies have been adopted that use plant morphological and physio...

Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning.

Plant science : an international journal of experimental plant biology
Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual s...

Enhancing genomic-based forward prediction accuracy in wheat by integrating UAV-derived hyperspectral and environmental data with machine learning under heat-stressed environments.

The plant genome
Integrating genomic, hyperspectral imaging (HSI), and environmental data enhances wheat yield predictions, with HSI providing detailed spectral insights for predicting complex grain yield (GY) traits. Incorporating HSI data with single nucleotide pol...