Learn what Optical Character Recognition is, what problems can be solved with OCR, and explore the approaches used by OCR algorithms to identify characters.
In this guide, we discuss what keypoint detection is, common architectures used for keypoint detection, and the high-level steps to build a keypoint detection model.
In this guide, we discuss what dataset distillation is, the methods through which a dataset can be distilled, and the applications of distilled datasets in computer vision.
In this guide, we discuss what knowledge distillation is, how it works, why knowledge distillation is useful, and the different methods of distilling knowledge from one model to another.
In this guide, we discuss what a Convolutional Neural Network (CNN) is, how they work, and discuss various different applications of CNNs in computer vision models.
In this blog post, we are going to introduce autoencoders
[https://en.wikipedia.org/wiki/Autoencoder], describe the several autoencoder
types that exist, and showcase their applications.
An autoencoder is
You'll hear the words "supervised learning" and "unsupervised learning" a lot in discussions about data science, machine learning, and other related fields. Being able to distinguish between supervised and unsupervised
