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 101–150 of 308 papers

TitleStatusHype
Reweighting Augmented Samples by Minimizing the Maximal Expected LossCode0
A Comparative Study on Efficiencies of Variants of Convolutional Neural Networks based on Image Classification TaskCode0
Learning Optimal Data Augmentation Policies via Bayesian Optimization for Image Classification TasksCode0
Domain Generalization with Fourier Transform and Soft ThresholdingCode0
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving AugmentationCode0
Siamese Networks for Cat Re-Identification: Exploring Neural Models for Cat Instance RecognitionCode0
Learning deep illumination-robust features from multispectral filter array imagesCode0
Learning to Compose Domain-Specific Transformations for Data AugmentationCode0
Batch Augmentation with Unimodal Fine-tuning for Multimodal LearningCode0
Efficient Method for Categorize Animals in the WildCode0
Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised LearningCode0
Compound Figure Separation of Biomedical Images with Side LossCode0
Language-Driven Dual Style Mixing for Single-Domain Generalized Object DetectionCode0
Isometric Transformations for Image Augmentation in Mueller Matrix PolarimetryCode0
CochCeps-Augment: A Novel Self-Supervised Contrastive Learning Using Cochlear Cepstrum-based Masking for Speech Emotion RecognitionCode0
Learning Convolutional Neural Networks using Hybrid Orthogonal Projection and EstimationCode0
BioImageLoader: Easy Handling of Bioimage Datasets for Machine LearningCode0
Albumentations: fast and flexible image augmentationsCode0
Improved Mixed-Example Data AugmentationCode0
Improving Fairness using Vision-Language Driven Image AugmentationCode0
A machine-generated catalogue of Charon's craters and implications for the Kuiper beltCode0
CIA: Controllable Image Augmentation Framework Based on Stable DiffusionCode0
Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairingCode0
Improving Performance of Federated Learning based Medical Image Analysis in Non-IID Settings using Image AugmentationCode0
Hybrid GAN and Fourier Transformation for SAR Ocean Pattern Image AugmentationCode0
Few-Shot Learning for Image Classification of Common FloraCode0
A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorchCode0
Genetic Learning for Designing Sim-to-Real Data AugmentationsCode0
Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic SegmentationCode0
Beyond Random Augmentations: Pretraining with Hard ViewsCode0
Long Tail Image Generation Through Feature Space Augmentation and Iterated LearningCode0
SAC-GAN: Structure-Aware Image CompositionCode0
Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging—0
Exploiting Partial Structural Symmetry For Patient-Specific Image Augmentation in Trauma Interventions—0
Camera-based method for the detection of lifted truck axles using convolutional neural networks—0
Explanatory Analysis and Rectification of the Pitfalls in COVID-19 Datasets—0
Exemplar-Free Continual Transformer with Convolutions—0
A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks—0
Evolving Loss Functions for Specific Image Augmentation Techniques—0
Evaluation and Comparison of Emotionally Evocative Image Augmentation Methods—0
Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems—0
Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images—0
Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network—0
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation—0
A Residual Encoder-Decoder Network for Segmentation of Retinal Image-Based Exudates in Diabetic Retinopathy Screening—0
Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification—0
Ensemble of Anchor-Free Models for Robust Bangla Document Layout Segmentation—0
Enhancing weed detection performance by means of GenAI-based image augmentation—0
Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified