Innovative vibrational spectroscopy research for forensic application
A Weber, B Hoplight, R Ogilvie, C Muro… - Analytical …, 2023 - ACS Publications
Forensic science is a unique field of study as it combines fundamental and applied research
to assist with matters of the criminal justice system. While other branches of science have a …
to assist with matters of the criminal justice system. While other branches of science have a …
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 …
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 …
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 …
Stochastic neighbor embedding feature-based hyperspectral image classification using 3d convolutional neural network
The ample amount of information from hyperspectral image (HSI) bands allows the non-
destructive detection and recognition of earth objects. However, dimensionality reduction …
destructive detection and recognition of earth objects. However, dimensionality reduction …
Wavemamba: Spatial-spectral wavelet mamba for hyperspectral image classification
Hyperspectral Imaging (HSI) has proven to be a powerful tool for capturing detailed spectral
and spatial information across diverse applications. Despite the advancements in Deep …
and spatial information across diverse applications. Despite the advancements in Deep …
An extensive review of hyperspectral image classification and prediction: techniques and challenges
G Tejasree, L Agilandeeswari - Multimedia Tools and Applications, 2024 - Springer
Abstract Hyperspectral Image Processing (HSIP) is an essential technique in remote
sensing. Currently, extensive research is carried out in hyperspectral image processing …
sensing. Currently, extensive research is carried out in hyperspectral image processing …
[HTML][HTML] Graph-infused hybrid vision transformer: Advancing GeoAI for enhanced land cover classification
Abstract Hyperspectral Image Classification (HSIC) is a challenging task due to the high-
dimensional nature of Hyperspectral Imaging (HSI) data and the complex relationships …
dimensional nature of Hyperspectral Imaging (HSI) data and the complex relationships …
SCS-Net: Sharpend cosine similarity based neural network for hyperspectral image classification
Hyperspectral image classification (HSIC) faces challenges in preserving high-frequency
features during downsampling and hierarchical filtering in the CNN architecture. To …
features during downsampling and hierarchical filtering in the CNN architecture. To …