19 citations · 35 across the 6 of their papers we have counts for
9 papers
A Learnable ScatterNet: Locally Invariant Convolutional Layers
Fergal Cotter, Nick Kingsbury
In this paper we explore tying together the ideas from Scattering Transforms and Convolutional Neural Networks (CNN) for Image Analysis by proposing a learnable ScatterNet. Previou…
Deep Learning in the Wavelet Domain
Fergal Cotter, Nick Kingsbury
This paper examines the possibility of, and the possible advantages to learning the filters of convolutional neural networks (CNNs) for image analysis in the wavelet domain. We are…
Generative ScatterNet Hybrid Deep Learning (G-SHDL) Network with Structural Priors for Semantic Image Segmentation
Amarjot Singh, Nick Kingsbury
This paper proposes a generative ScatterNet hybrid deep learning (G-SHDL) network for semantic image segmentation. The proposed generative architecture is able to train rapidly fro…
Visualizing and Improving Scattering Networks
Fergal Cotter, Nick Kingsbury
Scattering Transforms (or ScatterNets) introduced by Mallat are a promising start into creating a well-defined feature extractor to use for pattern recognition and image classifica…
Efficient Convolutional Network Learning using Parametric Log based Dual-Tree Wavelet ScatterNet
Amarjot Singh, Nick Kingsbury
We propose a DTCWT ScatterNet Convolutional Neural Network (DTSCNN) formed by replacing the first few layers of a CNN network with a parametric log based DTCWT ScatterNet. The Scat…
ScatterNet Hybrid Deep Learning (SHDL) Network For Object Classification
Amarjot Singh, Nick Kingsbury
The paper proposes the ScatterNet Hybrid Deep Learning (SHDL) network that extracts invariant and discriminative image representations for object recognition. SHDL framework is con…
Multi-Resolution Dual-Tree Wavelet Scattering Network for Signal Classification
Amarjot Singh, Nick Kingsbury
This paper introduces a Deep Scattering network that utilizes Dual-Tree complex wavelets to extract translation invariant representations from an input signal. The computationally…
Dual-Tree Wavelet Scattering Network with Parametric Log Transformation for Object Classification
Amarjot Singh, Nick Kingsbury
We introduce a ScatterNet that uses a parametric log transformation with Dual-Tree complex wavelets to extract translation invariant representations from a multi-resolution image.…
Convex Approaches to Model Wavelet Sparsity Patterns
Nikhil S Rao, Robert D. Nowak, Stephen J. Wright +1
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees(HMTs). However, in linear inverse problems such as deco…