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Found 6 papers, 0 papers with code
Multilayer deep feature extraction for visual texture recognition
The reason for using features from earlier convolutional layers is obtaining information that is less domain specific.
Fractal measures of image local features: an application to texture recognition
Here we propose a new method for the classification of texture images combining fractal measures (fractal dimension, multifractal spectrum and lacunarity) with local binary patterns.
VisGraphNet: a complex network interpretation of convolutional neural features
Here we propose and investigate the use of visibility graphs to model the feature map of a neural network.
An application of a pseudo-parabolic modeling to texture image recognition
In this work, we present a novel methodology for texture image recognition using a partial differential equation modeling.
A study on a feedforward neural network to solve partial differential equations in hyperbolic-transport problems
In this work we present an application of modern deep learning methodologies to the numerical solution of partial differential equations in transport models.
Numerical Analysis Numerical Analysis
Texture image classification based on a pseudo-parabolic diffusion model
This work proposes a novel method based on a pseudo-parabolic diffusion process to be employed for texture recognition.
