AIMC Topic: Hyperspectral Imaging

Clear Filters Showing 11 to 20 of 210 articles

Deep learning-based regression of food quality attributes using near-infrared spectroscopy and hyperspectral imaging: A review.

Food chemistry
Near-infrared (NIR) spectroscopy and hyperspectral imaging (HSI) are two popular non-destructive tools for food quality and safety inspection. For food quality attributes quantification, the key is to develop regression models to link the features (s...

Assessment of plant diversity index in degraded desert grassland using UAV hyperspectral multimodal data and Encoder-CNN.

Scientific reports
The biodiversity function of the desert steppe ecosystem faces many challenges under the pressure of climate change and human activities. Accurate and efficient assessment of plant diversity is critical for guiding desert steppe restoration efforts. ...

EchoMamba: A new Mamba model for fast and efficient hyperspectral image classification.

PloS one
The classification of hyperspectral images (HSI) is an important foundation in the field of remote sensing. Mamba architectures based on state space model (SSM) have shown great potential in the field of HSI processing due to their powerful long-rang...

Enhanced bi-branch deep learning network for in vivo hyperspectral imaging recognition of organs and tissues.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Hyperspectral imaging, as an emerging medical imaging technology, offers significant potential in biomedical research due to its ability in capturing rich spectral information. An enhanced bi-branch network integrating graph convolutional network (GC...

Leveraging potential of limpid attention transformer with dynamic tokenization for hyperspectral image classification.

PloS one
Hyperspectral data consists of continuous narrow spectral bands. Due to this, it has less spatial and high spectral information. Convolutional neural networks (CNNs) emerge as a highly contextual information model for remote sensing applications. Unf...

Application of an electronic tongue and hyperspectral imaging with a CNN-transformer fusion model for rapid detection of botanical origins of honey.

Analytical methods : advancing methods and applications
The botanical origin of honey significantly impacts its nutritional composition, quality, and price. Traditional identification methods are often complex, require expensive equipment, and are time-consuming. This article proposes a rapid detection me...

Deep learning-based multimodal fusion for quality prediction of chili paste using hyperspectral imaging and near-infrared spectroscopy.

Food chemistry
A deep learning-based intelligent multimodal system was developed to non-destructively evaluate chili paste quality by fusing color features extracted from hyperspectral images acquired by Hyperspectral Imaging (HSI), spectral features derived from H...

A hyperspectral imaging dataset and Grassmann manifold method for intraoperative pixel-wise classification of metastatic colon cancer in the liver.

Computers in biology and medicine
Hyperspectral imaging (HSI) holds significant potential for transforming the field of computational pathology. However, the number of HSI-based research studies remains limited, and in many cases, the advantages of HSI over traditional RGB imaging ha...

Hyperspectral imaging for trace cadmium prediction in lettuce leaves.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Cadmium (Cd) pollution presents a significant threat to the agricultural product control, and the development of detection technology for Cd content in lettuce has important application value. This study developed a nondestructive approach based on h...

Efficient wheat variety identification using Raman hyperspectral imaging in combination with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Wheat (Triticum aestivum L.) is recognized as a globally important staple crop, with its varietal differences influencing food processing, nutritional value, and agricultural productivity. Traditional identification methods are often considered ineff...