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

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Showing 76–100 of 308 papers

TitleStatusHype
An Interpretable Deep Learning Approach for Skin Cancer CategorizationCode0
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—0
Diversified in-domain synthesis with efficient fine-tuning for few-shot classificationCode1
SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World—0
CLAP: Isolating Content from Style through Contrastive Learning with Augmented PromptsCode1
Resolution- and Stimulus-agnostic Super-Resolution of Ultra-High-Field Functional MRI: Application to Visual Studies—0
OASIS: Offsetting Active Reconstruction Attacks in Federated Learning—0
Geometric Data Augmentations to Mitigate Distribution Shifts in Pollen Classification from Microscopic Images—0
Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques—0
Improving Fairness using Vision-Language Driven Image AugmentationCode0
DT/MARS-CycleGAN: Improved Object Detection for MARS Phenotyping Robot—0
Image Augmentation with Controlled Diffusion for Weakly-Supervised Semantic Segmentation—0
Leveraging Image Augmentation for Object Manipulation: Towards Interpretable Controllability in Object-Centric Learning—0
Augmenting Vision-Based Human Pose Estimation with Rotation Matrix—0
Beyond Random Augmentations: Pretraining with Hard ViewsCode0
Randomize to Generalize: Domain Randomization for Runway FOD Detection—0
Selective Volume Mixup for Video Action RecognitionCode0
Domain Generalization with Fourier Transform and Soft ThresholdingCode0
Improved Breast Cancer Diagnosis through Transfer Learning on Hematoxylin and Eosin Stained Histology Images—0
Improving Deep Learning-based Defect Detection on Window Frames with Image Processing Strategies—0
MLN-net: A multi-source medical image segmentation method for clustered microcalcifications using multiple layer normalizationCode0
Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning—0
Ensemble of Anchor-Free Models for Robust Bangla Document Layout Segmentation—0
Handwritten image augmentation—0
Exemplar-Free Continual Transformer with Convolutions—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified