Oreolorun is a machine learning engineer with particular interest in computer vision applications. He loves to write about nuanced concepts in machine learning in an easy to understand manner.
In this article, we took a look at working with custom datasets in PyTorch to curated a custom dataset via web scraping, load and label it, and created a PyTorch dataset from it.
In this tutorial we show how to collect image data from the web to use in your computer vision, deep learning projects on Paperspace.
In this article, we will be taking a look at what exactly constitutes images in a digital space so as to try to better understand and handle them, and thus improve understanding of processes and concepts in computer vision in general.
In this article, we explore concepts related to convolutional neural network architectures with the intention of building our understanding enough to create and understand the capabilities of an AlexNet model, from scratch.
In this article, we take a look at 1 x 1 convolution not only as a down-sampling tool, but also its many other potential uses with convolutional neural networks, such as dimensionality reduction or adding non-linearity.
This blog details different techniques for filtering image data and explores what these filters actually do to an image as it passes through the layers of a Convolutional Neural Network (CNN). https://blog.paperspace.com/filters-in-convolutional-neural-networks/
In this article, we explore how and why we use padding in CNNs in computer vision tasks. We'll then jump into a full coding demo showing the utility of padding.
