Data Augmentation

Advanced Data Augmentation Strategies

Deep Learning models love data. There is no better way to quickly boost the performance of your deep learning model than to add more training data to it. However, collecting and labeling data can be…

Data Augmentation Experimentation

This follows up on my earlier article about data augmentation: Data Augmentation using Fastai. Invariance is the ability of convolutional neural networks to classify objects even when they are placed…...

Data Augmentation and Images

One of the best ways to improve the performance of a Deep Learning model is to add more data to the training set. Aside from gathering more instances from the wild that are representative of the…

Data augmentation

Overview This tutorial demonstrates data augmentation: a technique to increase the diversity of your training set by applying random (but realistic) transformations, such as image rotation. You will l...

Image Data Augmentations

Curation of image data augmentation methods in the literature with highlights from the papers Continue reading on Towards Data Science

Image Augmentation

Part A: Introduction to Image Augmentation, various augmentation techniques, and its implementation through available libraries. Part B: Building and training a PyTorch model and analyzing the effect…...

Data Augmentation: What, Why and How……

Data augmentation is a regularization technique like Lasso, Hinge, L1, and L2 regularizations, it also participates with great help during any machine learning model training process. In general…

Unsupervised Data Augmentation

The more data we have, the better the performance we can achieve. However, it is very too luxury to annotate a large amount of training data. Therefore, proper data augmentation is useful to boost up…...

Image Augmentation

In Section 8.1 , we mentioned that large datasets are a prerequisite for the success of deep neural networks in various applications. Image augmentation generates similar but distinct training example...

Data Augmentation in Deep Learning

Whenever you build and train a model for a machine learning task, regardless of its being a classification or regression one, your final goal is to make reliable predictions on new, never seen before…...

Maximizing the Impact of Data Augmentation: Effective Techniques and Best Practices

Data augmentation is a popular technique in machine learning that involves creating new data from existing data by making various… Continue reading on Towards AI

1000x Faster Data Augmentation

In this blog post we introduce Population Based Augmentation (PBA), an algorithm that quickly and efficiently learns a state-of-the-art approach to augmenting data for neural network training. PBA…

Data Augmentation With AugLy

All-in-one augmentation packages for machine learning Continue reading on Better Programming

Augmenting Images for Deep Learning

Using Python to augment data by flipping, adjusting brightness, color jitter and random noise Continue reading on Towards Data Science

Balancing the Regularization Effect of Data Augmentation

When training neural networks, data augmentation is one of the most commonly used pre-processing techniques. The word “augmentation” which literally means “the action or process of making or becoming…...

Data Augmentation with Copy-Paste Technique

One of the overarching themes for Data Science at Doma is generalizability. This is very important for the successful implementation of our machine learning models in our products due to the wide…

Data Augmentation in Medical Images

The popularization of machine learning has changed our world in wonderful ways. Some notable applications of machine learning allow us to do the previously unthinkable, like determining if an image…

Deep learning topics — data augmentation

Why do we need data augmentation?. “Deep learning topics — data augmentation” is published by Sophia Yang in Analytics Vidhya.

Image Augmentation using Keras

Data preparation is required when working with neural network and deep learning models. Increasingly data augmentation is also required on more complex object recognition tasks. Data augmentation…

Data Augmentation using Fastai

There are 5 steps to avoiding over fitting; getting more data, data augmentation, using generalized architectures, regularization and reducing architecture complexity As mentioned above data…

Data Augmentation techniques in Python

In this article, we will explore different data augmentation techniques in Python using imgaug library Image augmentation is a very powerful technique used to artificially create variations in…

Data Augmentations in Torchvision

This blog aims to compare and familiarise with different data transformations techniques used by the research community Image by author. Introduction Why do we need data augmentation? Data augmentati...

A Short Survey on Implicit Data Augmentation

Data augmentation is a popular technique used to increase the generalizability of a possibly overfitting model. By generating additional training data and exposing the model to different versions of…