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 3140 of 308 papers

TitleStatusHype
Diffusion-Enhanced Test-time Adaptation with Text and Image AugmentationCode2
SGIA: Enhancing Fine-Grained Visual Classification with Sequence Generative Image Augmentation0
Hybrid GAN and Fourier Transformation for SAR Ocean Pattern Image AugmentationCode0
Swin Transformer with Enhanced Dropout and Layer-wise Unfreezing for Facial Expression Recognition in Mental Health DetectionCode1
BGM: Background Mixup for X-ray Prohibited Items Detection0
Enhancing Document AI Data Generation Through Graph-Based Synthetic Layouts0
Enhancing weed detection performance by means of GenAI-based image augmentation0
Spatially Visual Perception for End-to-End Robotic Learning0
CIA: Controllable Image Augmentation Framework Based on Stable DiffusionCode0
Isometric Transformations for Image Augmentation in Mueller Matrix PolarimetryCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0Unverified