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 1–25 of 308 papers

TitleStatusHype
Detectron2 Object Detection & Manipulating Images using CartoonizationCode4
UniMERNet: A Universal Network for Real-World Mathematical Expression RecognitionCode3
AutoAugment: Learning Augmentation Policies from DataCode3
Differentiable Data Augmentation with KorniaCode3
Enhance Then Search: An Augmentation-Search Strategy with Foundation Models for Cross-Domain Few-Shot Object DetectionCode2
Random Erasing Data AugmentationCode2
Deep PCB To COCO ConvertorCode2
XoFTR: Cross-modal Feature Matching TransformerCode2
CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documentsCode2
Diffusion-Enhanced Test-time Adaptation with Text and Image AugmentationCode2
When Large Multimodal Models Confront Evolving Knowledge:Challenges and PathwaysCode2
A Survey on Data Augmentation in Large Model EraCode2
An Open-source Tool for Hyperspectral Image Augmentation in TensorflowCode1
Adversarial Policy Gradient for Deep Learning Image AugmentationCode1
Adversarial Instance Augmentation for Building Change Detection in Remote Sensing ImagesCode1
Diversified in-domain synthesis with efficient fine-tuning for few-shot classificationCode1
Diversify Your Vision Datasets with Automatic Diffusion-Based AugmentationCode1
An Efficient and Scalable Deep Learning Approach for Road Damage DetectionCode1
CLAP: Isolating Content from Style through Contrastive Learning with Augmented PromptsCode1
Anatomical Data Augmentation via Fluid-based Image RegistrationCode1
Data Augmentation Based Malware Detection using Convolutional Neural NetworksCode1
Data Augmentation for Scene Text RecognitionCode1
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural NetworksCode1
Can AI help in screening Viral and COVID-19 pneumonia?Code1
AugNet: End-to-End Unsupervised Visual Representation Learning with Image AugmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified