Hyperspectral image classification—Traditional to deep models: A survey for future prospects
Hyperspectral imaging (HSI) has been extensively utilized in many real-life applications
because it benefits from the detailed spectral information contained in each pixel. Notably …
because it benefits from the detailed spectral information contained in each pixel. Notably …
Conventional to deep ensemble methods for hyperspectral image classification: A comprehensive survey
Hyperspectral image classification (HSIC) has become a hot research topic. Hyperspectral
imaging (HSI) has been widely used in a wide range of real-world application areas due to …
imaging (HSI) has been widely used in a wide range of real-world application areas due to …
A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers
Hyperspectral Image Classification (HSC) is a challenging task due to the high
dimensionality and complex nature of Hyperspectral (HS) data. Traditional Machine …
dimensionality and complex nature of Hyperspectral (HS) data. Traditional Machine …
Rapid and non-destructive cinnamon authentication by NIR-hyperspectral imaging and classification chemometrics tools
JP Cruz-Tirado, YL Brasil, AF Lima, HA Pretel… - … Acta Part A: Molecular …, 2023 - Elsevier
Cinnamon is a valuable aromatic spice widely used in pharmaceutical and food industry.
Commonly, two-cinnamon species are available in the market, Cinnamomum verum (true …
Commonly, two-cinnamon species are available in the market, Cinnamomum verum (true …
Spatial spectral transformer with conditional position encoding for hyperspectral image classification
In Transformer-based hyperspectral image classification (HSIC), predefined positional
encodings (PEs) are crucial for capturing the order of each input token. However, their …
encodings (PEs) are crucial for capturing the order of each input token. However, their …
Hyperspectral imaging for bloodstain identification
Blood is key evidence to reconstruct crime scenes in forensic sciences. Blood identification
can help to confirm a suspect, and for that reason, several chemical methods are used to …
can help to confirm a suspect, and for that reason, several chemical methods are used to …
A disjoint samples-based 3D-CNN with active transfer learning for hyperspectral image classification
Convolutional neural networks (CNNs) have been extensively studied for hyperspectral
image classification (HSIC). However, CNNs are critically attributed to a large number of …
image classification (HSIC). However, CNNs are critically attributed to a large number of …
Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants
Preserving red-chili quality is of utmost importance in which the authorities demand quality
techniques to detect, classify, and prevent it from impurities. For example, salt, wheat flour …
techniques to detect, classify, and prevent it from impurities. For example, salt, wheat flour …
Fusing transformers in a tuning fork structure for hyperspectral image classification across disjoint samples
The 3-D swin transformer (3DST) and spatial–spectral transformer (SST) each excel in
capturing distinct aspects of image information: the 3DST with hierarchical attention and …
capturing distinct aspects of image information: the 3DST with hierarchical attention and …
(2+ 1) D Extreme Xception Net for Hyperspectral Image Classification
3-D CNNs have demonstrated their capability to capture intricate nonlinear relationships
within hyperspectral images (HSIs). However, the computational complexity of 3-D CNNs …
within hyperspectral images (HSIs). However, the computational complexity of 3-D CNNs …