Data Augmentation

Albumentations is a Python library for image augmentation in deep learning, enhancing model training with diverse image transformations.

AugLy is an open-source library for augmenting audio, video, and image data for machine learning tasks.

AutoAugment is an automated technique for enhancing training datasets in machine learning.

CutMix is a data augmentation technique that combines images and labels for better model training.

CutMix Augmentation is a data augmentation technique combining images for improved model training.

Cutout Augmentation is a data augmentation technique used to enhance model robustness by randomly removing parts of an image.

A data augmentation pipeline enhances training datasets by applying various transformations to improve AI model performance.

GridMask is a data augmentation technique for enhancing the robustness of neural networks by masking parts of input images.

Jitter augmentation is a technique used to improve the robustness of AI models by simulating variations in data timing.

Manifold Mixup is a data augmentation technique that improves neural network training by blending input data and their labels.

RandAugment is a simple yet effective data augmentation technique for improving machine learning model performance.