Near Infrared Hyperspectral Image Analysis Using R. Part 5: Animated Visualisation of Hyperspectral Data Using R and ImageJ

NIR news ◽  
2014 ◽  
Vol 25 (7) ◽  
pp. 15-17 ◽  
Author(s):  
Y. Dixit ◽  
R. Cama ◽  
C. Sullivan ◽  
L. Alvarez Jubete ◽  
A. Ktenioudaki
Keyword(s):  
Image Analysis ◽  
Near Infrared ◽  
Hyperspectral Image ◽  
Hyperspectral Data ◽  
Hyperspectral Image Analysis

Identification of Fragmented Bones and Their State of Preservation Using near Infrared Hyperspectral Image Analysis

2013 ◽  
Vol 21 (6) ◽  
pp. 459-466 ◽  
Author(s):  
Johan Linderholm ◽  
Juan Antonio Fernández Pierna ◽  
Damien Vincke ◽  
Pierre Dardenne ◽  
Vincent Baeten
Keyword(s):  
Image Analysis ◽  
Near Infrared ◽  
Hyperspectral Image ◽  
Hyperspectral Image Analysis

scholarly journals Automatic near-infrared hyperspectral image analysis of copper concentrates

2019 ◽  
Vol 52 (14) ◽  
pp. 94-98
Author(s):  
Pablo A. Coelho ◽  
Claudio Sandoval ◽  
Jonnathan Alvarez ◽  
Ignacio Sanhueza ◽  
Cristofher Godoy ◽  
...  
Keyword(s):  
Image Analysis ◽  
Near Infrared ◽  
Hyperspectral Image ◽  
Hyperspectral Image Analysis

Classification of Sound and Stained Wheat Grains Using Visible and near Infrared Hyperspectral Image Analysis

2007 ◽  
Vol 15 (6) ◽  
pp. 351-358 ◽  
Author(s):  
M. Berman ◽  
P.M. Connor ◽  
L.B. Whitbourn ◽  
D.A. Coward ◽  
B.G. Osborne ◽  
...  
Keyword(s):  
Image Analysis ◽  
Near Infrared ◽  
Hyperspectral Image ◽  
Wheat Grains ◽  
Hyperspectral Image Analysis

scholarly journals Multilayered autoencoders in problems of hyperspectral image analysis and processing

2021 ◽  
pp. 1-21
Author(s):  
Margarita Georgievna Kuzmina
Keyword(s):  
Image Analysis ◽  
Hyperspectral Image ◽  
Spectral Curve ◽  
Image Data ◽  
Image Features ◽  
Hyperspectral Data ◽  
Spectral Information ◽  
Data Set ◽  
Hyperspectral Image Analysis ◽  
Deep Image

A model of five-layered autoencoder (stacked autoencoder, SAE) is suggested for deep image features extraction and deriving compressed hyperspectral data set specifying the image. Spectral cost function, dependent on spectral curve forms of hyperspectral image, has been used for the autoencoder tuning. At the first step the autoencoder capabilities will be tested based on using pure spectral information contained in image data. The images from well known and widely used hyperspectral databases (Indian Pines, Pavia University и KSC) are planned to be used for the model testing.

scholarly journals Trends in Deep Learning for Medical Hyperspectral Image Analysis

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Uzair Khan ◽  
Sidike Paheding ◽  
Colin Elkin ◽  
Vijay Devabhaktuni
Keyword(s):  
Image Analysis ◽  
Deep Learning ◽  
Hyperspectral Image ◽  
Hyperspectral Image Analysis
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