Abstract: Convolutional neural networks are built upon simple but useful convolution modules. The traditional convolution has a limitation on feature extraction and object localization due to its ...

A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...

A moving-average filter can address white noise in the time domain but performs poorly in the frequency domain. In part 1 of this series, we defined convolution, denoted by the * symbol, and looked at ...

This project involves implementing the forward pass of an 18-layer Convolutional Neural Network (CNN) in MATLAB for object detection. The goal is to classify 32x32x3 images into one of ten categories, ...

Abstract: In natural images, information is conveyed at different frequencies where higher frequencies are usually encoded with fine details and lower frequencies are usually encoded with global ...

In seismic exploration, dense and evenly spatial sampled seismic traces are crucial for successful implementation of most seismic data processing and interpretation algorithms. Recently, numerous ...

When looking at the code you might realize there's a similarity to the autocorrelation / cross correlation demo app. :) Please be aware that you need Matlab and its Symbolic Math Toolbox (mainly for ...