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 251260 of 308 papers

TitleStatusHype
An Open-source Tool for Hyperspectral Image Augmentation in TensorflowCode1
Can AI help in screening Viral and COVID-19 pneumonia?Code1
Learn to Augment: Joint Data Augmentation and Network Optimization for Text RecognitionCode1
Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging0
Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation0
Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy0
Automatic phantom test pattern classification through transfer learning with deep neural networks0
Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems0
What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network PerformanceCode1
Decision Support System for Detection and Classification of Skin Cancer using CNN0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0Unverified