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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 308 papers

TitleStatusHype
Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging—0
Image Augmentation for Object Image Classification Based On Combination of PreTrained CNN and SVM—0
Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References—0
Image Augmentation for Satellite Images—0
Image augmentation improves few-shot classification performance in plant disease recognition—0
Image augmentation with conformal mappings for a convolutional neural network—0
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations—0
AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Image—0
Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning—0
Unified Framework for Histopathology Image Augmentation and Classification via Generative Models—0
Attention W-Net: Improved Skip Connections for better Representations—0
A convolutional neural network of low complexity for tumor anomaly detection—0
How Quality Affects Deep Neural Networks in Fine-Grained Image Classification—0
How to Augment for Atmospheric Turbulence Effects on Thermal Adapted Object Detection Models?—0
GANet-Seg: Adversarial Learning for Brain Tumor Segmentation with Hybrid Generative Models—0
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection—0
GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification—0
Game State Learning via Game Scene Augmentation—0
A Technical Report for VIPriors Image Classification Challenge—0
A Methodology to Identify Cognition Gaps in Visual Recognition Applications Based on Convolutional Neural Networks—0
Image Augmentation Agent for Weakly Supervised Semantic Segmentation—0
Attention-Driven Lightweight Model for Pigmented Skin Lesion Detection—0
Image Augmentation Based Momentum Memory Intrinsic Reward for Sparse Reward Visual Scenes—0
Generative Adversarial U-Net for Domain-free Medical Image Augmentation—0
Fuzzy Semantic Segmentation of Breast Ultrasound Image with Breast Anatomy Constraints—0
Show:102550
← PrevPage 6 of 13Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified