INSIDDE THz Toolbox v0.2

INSIDDE THz Toolbox provides various methods for THz image analysis.
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Updated 27 Mar 2015

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INSIDDE THz Toolbox includes various image processing and machine learning techniques to analyze THz images. The toolbox includes implementations of Gaussian deconvolution, anisotropic filtering, image gradient estimation, independent components analysis, texton histograms, multi-scale structure tensors, logistic regression, Gaussian process regression, autoencoding, deep autoencoding, and large-margin triplet learning, as well as an automatic system for thread-level canvas analysis.
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 600849.

Cite As

Hamdi Dibeklioglu (2024). INSIDDE THz Toolbox v0.2 (https://www.mathworks.com/matlabcentral/fileexchange/49437-insidde-thz-toolbox-v0-2), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
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INSIDDE_thz_toolbox_v0.2/

INSIDDE_thz_toolbox_v0.2/canvas_analysis/

INSIDDE_thz_toolbox_v0.2/filtering/

INSIDDE_thz_toolbox_v0.2/ica/

INSIDDE_thz_toolbox_v0.2/learning/autoencoder/

INSIDDE_thz_toolbox_v0.2/learning/gpreg/

INSIDDE_thz_toolbox_v0.2/learning/lmtl/

INSIDDE_thz_toolbox_v0.2/learning/logreg/

INSIDDE_thz_toolbox_v0.2/modelling/

INSIDDE_thz_toolbox_v0.2/modelling/netlab/

INSIDDE_thz_toolbox_v0.2/structure_tensor/

INSIDDE_thz_toolbox_v0.2/texton_histograms/

Version Published Release Notes
1.2.0.0

+ Autoencoding
+ Deep autoencoding
+ Texton histograms
+ Multi-scale structure tensors
+ Large-margin triplet learning

1.1.0.0

-

1.0.0.0