Non-destructive techniques for the analysis and evaluation of meat quality and safety: A review
X Wu, X Liang, Y Wang, B Wu, J Sun - Foods, 2022 - mdpi.com
With the continuous development of economy and the change in consumption concept, the
demand for meat, a nutritious food, has been dramatically increasing. Meat quality is tightly …
demand for meat, a nutritious food, has been dramatically increasing. Meat quality is tightly …
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 …
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 …
A fast and compact hybrid CNN for hyperspectral imaging-based bloodstain classification
In forensic sciences, blood is a shred of essential evidence for reconstructing crime scenes.
Blood identification and classification may help to confirm a suspect, although several …
Blood identification and classification may help to confirm a suspect, although several …
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 …