AIMC Topic: Hyperspectral Imaging

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Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review.

Journal of agricultural and food chemistry
Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Traditional chemical analysis and physical measurement techniques are reliable, they are also time-consuming, costly, and susceptible to environmental a...

Synergizing meat science and interpretable AI: Quantifying crispness gradients for quality authentication of Tilapia fillet processing.

Food chemistry
Crispy tilapia has become a popular aquatic product due to its unique texture and high market demand. However, fillets at different stages of crispness vary significantly in nutritional value and taste, directly affecting product quality and consumer...

Multimodal imaging platform for enhanced tumor resection in neurosurgery: integrating hyperspectral and pCLE technologies.

International journal of computer assisted radiology and surgery
PURPOSE: This work presents a novel multimodal imaging platform that integrates hyperspectral imaging (HSI) and probe-based confocal laser endomicroscopy (pCLE) for improved brain tumor identification during neurosurgery. By combining these two modal...

Machine learning-combined hyperspectral imaging analysis for the non-destructive identification of wheat flours with varying gluten strengths.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study aimed to non-destructively identify wheat flours with different gluten strengths through the application of machine learning-combined hyperspectral imaging analysis. The performance of this approach was compared to conventional instrumenta...

ULST: U-shaped LeWin Spectral Transformer for virtual staining of pathological sections.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
At present, pathological section staining faces several challenges, including complex sample preparation and stringent infrastructure requirements. Virtual staining methods utilizing deep neural networks to automatically generate stained images are g...

Fluorescence hyperspectral imaging for detection of selenium content in lettuce leaves under cadmium-free and cadmium environments.

Food chemistry
This study aimed to investigate the feasibility of detecting selenium content in lettuce leaves under complex environments (cadmium-free and cadmium environments) using fluorescence hyperspectral imaging (FHSI). Accordingly, multimodal difference-awa...

Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception-ResNet Model.

Toxins
Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses significant health risks. Therefore, a rapid and non-destructive detection method is crucial to detect aflatoxin B1-contaminated almonds to ensure food ...

Progress in machine learning-supported electronic nose and hyperspectral imaging technologies for food safety assessment: A review.

Food research international (Ottawa, Ont.)
The growing concern over food safety, driven by threats such as food contaminations and adulterations has prompted the adoption of advanced technologies like electronic nose (e-nose) and hyperspectral imaging (HSI), which are increasingly enhanced by...

Mapping acrylamide content in potato chips using near-infrared hyperspectral imaging and chemometrics.

Food chemistry
This study investigated the potential of near-infrared hyperspectral imaging (NIR-HSI) for the prediction of acrylamide content in potato chips. A total of 300 tubers from two potato varieties (Agria and Jaerla) grown in two seasons and processed und...

Nondestructive detection of cadmium content in oilseed rape leaves under different silicon environments using deep transfer learning and Vis-NIR hyperspectral imaging.

Food chemistry
In this paper, a transfer stack denoising autoencoder (T-SDAE) algorithm is proposed to implement the migration of cadmium (Cd) prediction depth characteristic model of oilseed rape leaves in different silicon environments. Stacked denoising autoenco...