Abstract A rigid-motion scattering computes adaptive invariants along translations and rotations, with a deep convolutional network. Convolutions are calculated on the rigid-motion group, with wavelets defined on the translation and rotation variables. It preserves joint rotation and translation information, while providing global invariants at any desired scale. Texture classification is studied, through the characterization of stationary processes from a single realization. State-of-the-art results are obtained on multiple texture data bases, with important rotation and scaling variabilities. Keywords Deep network · scattering · wavelet · rigid-motion · texture · classification Work supported by ANR 10-BLAN-0126 and Advance
We present texture operators encoding class-specific local organizations of image directions (LOIDs)...
This paper aims to provide a deep neural network (DNN) considering the statistical properties of dat...
Déposée Novembre 2012.This thesis addresses the problem of pattern and texture recognition from a ma...
An affine invariant representation is constructed with a cascade of invariants, which preserves info...
Abstract—A wavelet scattering network computes a translation invariant image representation which is...
Image classification is the problem of assigning a label that best describes the content of unknown ...
This thesis addresses the problem of pattern and texture recognition from a mathematical perspective...
this paper, the issue of rotation-invariance for texture is studied. The CWT is well adapted to perf...
Dynamic Texture (DT) can be considered as an extension of the static texture additionally comprising...
We present a method for learning discriminative filters using a shallow Convolutional Neural Network...
We introduce a deep scattering network, which computes invariants with iterated con-tractions adapte...
Texture classification is an important research topic in image processing. In 2012, scattering trans...
Abstract—This paper studies the problem of 3-D rigid-motion-invariant texture discrimination for dis...
International audienceDeep convolutional neural networks accuracy is heavily impacted by rotations o...
This article proposes the modelling and analysis of image texture using an extension of a locally st...
We present texture operators encoding class-specific local organizations of image directions (LOIDs)...
This paper aims to provide a deep neural network (DNN) considering the statistical properties of dat...
Déposée Novembre 2012.This thesis addresses the problem of pattern and texture recognition from a ma...
An affine invariant representation is constructed with a cascade of invariants, which preserves info...
Abstract—A wavelet scattering network computes a translation invariant image representation which is...
Image classification is the problem of assigning a label that best describes the content of unknown ...
This thesis addresses the problem of pattern and texture recognition from a mathematical perspective...
this paper, the issue of rotation-invariance for texture is studied. The CWT is well adapted to perf...
Dynamic Texture (DT) can be considered as an extension of the static texture additionally comprising...
We present a method for learning discriminative filters using a shallow Convolutional Neural Network...
We introduce a deep scattering network, which computes invariants with iterated con-tractions adapte...
Texture classification is an important research topic in image processing. In 2012, scattering trans...
Abstract—This paper studies the problem of 3-D rigid-motion-invariant texture discrimination for dis...
International audienceDeep convolutional neural networks accuracy is heavily impacted by rotations o...
This article proposes the modelling and analysis of image texture using an extension of a locally st...
We present texture operators encoding class-specific local organizations of image directions (LOIDs)...
This paper aims to provide a deep neural network (DNN) considering the statistical properties of dat...
Déposée Novembre 2012.This thesis addresses the problem of pattern and texture recognition from a ma...