List of useful data augmentation resources. You will find here some not common techniques, libraries, links to GitHub repos, papers, and others.

RAD: Reinforcement Learning with Augmented Data

A simpler way of reading and augmenting image segmentation data into TensorFlow

Code for You Only Cut Once: Boosting Data Augmentation with a Single Cut, ICML 2022.

✍️ Convolutional Recurrent Neural Network in Pytorch | Text Recognition

SuperpixelGridMasks is an approach for sensor-based data augmentation towards image classification tasks and so on.

[KDD23] Official PyTorch implementation for "Improving Conversational Recommendation Systems via Counterfactual Data Simulation".

A toolkit to augment audios (e.g. noise, reverb, distort, speedup, packet loss, farfield effects).

This repository contains projects in the field of Deep Learning

Image Manipulation

This project implements an image classification model using Convolutional Neural Networks (CNN) to classify images from the CIFAR-10 dataset. The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes, with 6,000 images per class. The classes include airplanes, automobiles, birds, cats, deer, dogs, frogs, horses, and trucks.