SOTAVerified

Image Augmentation

Image Augmentation is a data augmentation method that generates more training data from the existing training samples. Image Augmentation is especially useful in domains where training data is limited or expensive to obtain like in biomedical applications.

Source: Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairing

( Image credit: Kornia )

Papers

Showing 261270 of 308 papers

TitleStatusHype
Kornia: an Open Source Differentiable Computer Vision Library for PyTorchCode1
ANDA: A Novel Data Augmentation Technique Applied to Salient Object DetectionCode0
Implicit Semantic Data Augmentation for Deep NetworksCode1
Fuzzy Semantic Segmentation of Breast Ultrasound Image with Breast Anatomy Constraints0
Adversarial Policy Gradient for Deep Learning Image AugmentationCode1
Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairingCode0
A CNN toolbox for skin cancer classification0
Synthetic Image Augmentation for Improved Classification using Generative Adversarial Networks0
Efficient Method for Categorize Animals in the WildCode0
Slot Based Image Augmentation System for Object Detection0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0Unverified