Data Augmentation

Data augmentation is a strategy that enables practitioners to significantly increase the diversity of data available for training models, without actually collecting new data. Data augmentation techniques such as cropping, padding, and horizontal flipping are commonly used to train large neural networks.


Data Augmentation | How to use Deep Learning With Limited Data
This article is a comprehensive review of Data Augmentation techniques for Deep Learning, specific to images.
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A Visual Survey of Data Augmentation in NLP
An extensive overview of text data augmentation techniques for Natural Language Processing
natural-language-processing data-augmentation tutorial article


Automating the Art of Data Augmentation
Learning to Compose Domain-Specific Transformations for Data Augmentation
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Data augmentation recipes in tf.keras image-based models
Learn about different ways of doing data augmentation when training an image classifier in tf.keras.
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Automating Data Augmentation: Practice, Theory and New Direction
A new framework for exploiting data augmentation to patch a flawed model and improve performance on crucial subpopulation of data.
data-augmentation tutorial article
Image Augmentations for GAN Training
We systematically study the effectiveness of various existing augmentation techniques for GAN training in a variety of settings.
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Automatic Data Augmentation for Generalization in Deep RL
We compare three approaches for automatically finding an appropriate augmentation combined with two novel regularization terms for the policy and value ...
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Training Generative Adversarial Networks with Limited Data
An adaptive discriminator augmentation mechanism that significantly stabilizes training in limited data regimes.
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Multi-target in Albumentations
Many images, many masks, bounding boxes, and key points. How to transform them in sync?
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Test-Time Data Augmentation
Tutorial on how to properly implement test-time image data augmentation in a production environment with limited computational resources.
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A system for quickly generating training data with weak supervision.
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Tabular Data Augmentation & Feature Engineering.
data-augmentation tabular-data tabular table
NLP Libraries
A Python framework for building adversarial attacks on NLP models.
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Improving Short Text Classification through Global Augmentation Methods
data-augmentation natural-language-processing library code
A Python library for replacing the missing variation in your text data.
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CV Libraries
SOLT: Data Augmentation for Deep Learning
Data augmentation library for Deep Learning, which supports images, segmentation masks, labels and key points.
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Fast image augmentation library and easy to use wrapper around other libraries.
data-augmentation computer-vision demo notebook
Image augmentation library in Python for machine learning.
data-augmentation computer-vision library code
CLoDSA: A Tool for Augmentation in Computer Vision tasks
CLoDSA is an open-source image augmentation library for object classification, localization, detection, semantic segmentation and instance segmentation. It ...
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TF Sprinkles
Fast and efficient sprinkles augmentation implemented in TensorFlow.
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Data augmentation recipes in tf.keras image-based models
Learn about different ways of doing data augmentation when training an image classifier in tf.keras.
image-classification deep-learning data-augmentation computer-vision
Other Libraries
A Python library for audio data augmentation. Inspired by albumentations.
data-augmentation audio library code
A Python package for time series augmentation.
time-series data-augmentation tsaug code
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