The left column shows the original GLCMs created from the cerebellum region in Fig 3, for different quantization levels. The right column shows the invariant GLCMs for the same quantization levels. The original GLCMs are normalized so that the sum is 1, whereas the invariant features are normalized so that the volume of the GLCM is 1.</p
Example of how the GLCM is calculated for a given 4x4 pixel image (a) with the corresponding numeric...
<p>(A) An example set of generative fields , for ( pixels). Due to the normalization, different rec...
<p>Top row: cartoon of a divisive normalization model that accounts for surround modulation of V1 re...
Synthetic GLCMs generated as bivariate Gaussian distributions, for two different quantization levels...
In a 4 × 4 image, three gray-levels are represented by numerical values from 1 to 3. The GLCM is con...
Haralick texture features are common texture descriptors in image analysis. To compute the Haralick ...
<p>(<b>A</b>)–(<b>C</b>) Top row: GLM STRFs estimated from recorded responses to ml noise (Kn) and s...
A: Varying degrees of change in neural encoding as a function of a change in context. With a change ...
MA plot for high intensity probesets when all probesets are normalized (grey) and when only the high...
Haralick texture features are common texture descriptors in image analysis. To compute the Haralick ...
Texture features were computed for a range of quantization gray-levels from a region in the cerebell...
The heatmaps show the accuracy of logistic regression models trained on one quantization gray-level ...
Matlab code in this directory computes the results published in: Heeger DJ, Zemlianova KO, A recurre...
Calculates grey level co-occurrence matrix (GLCM) based texture measures (Hall-Beyer (2017) ; Harali...
<p>Single group VBM analysis with additional covariates (PCs): the statistical map represents the co...
Example of how the GLCM is calculated for a given 4x4 pixel image (a) with the corresponding numeric...
<p>(A) An example set of generative fields , for ( pixels). Due to the normalization, different rec...
<p>Top row: cartoon of a divisive normalization model that accounts for surround modulation of V1 re...
Synthetic GLCMs generated as bivariate Gaussian distributions, for two different quantization levels...
In a 4 × 4 image, three gray-levels are represented by numerical values from 1 to 3. The GLCM is con...
Haralick texture features are common texture descriptors in image analysis. To compute the Haralick ...
<p>(<b>A</b>)–(<b>C</b>) Top row: GLM STRFs estimated from recorded responses to ml noise (Kn) and s...
A: Varying degrees of change in neural encoding as a function of a change in context. With a change ...
MA plot for high intensity probesets when all probesets are normalized (grey) and when only the high...
Haralick texture features are common texture descriptors in image analysis. To compute the Haralick ...
Texture features were computed for a range of quantization gray-levels from a region in the cerebell...
The heatmaps show the accuracy of logistic regression models trained on one quantization gray-level ...
Matlab code in this directory computes the results published in: Heeger DJ, Zemlianova KO, A recurre...
Calculates grey level co-occurrence matrix (GLCM) based texture measures (Hall-Beyer (2017) ; Harali...
<p>Single group VBM analysis with additional covariates (PCs): the statistical map represents the co...
Example of how the GLCM is calculated for a given 4x4 pixel image (a) with the corresponding numeric...
<p>(A) An example set of generative fields , for ( pixels). Due to the normalization, different rec...
<p>Top row: cartoon of a divisive normalization model that accounts for surround modulation of V1 re...