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 251–275 of 308 papers

TitleStatusHype
An Empirical Study of Validating Synthetic Data for Text-Based Person RetrievalCode0
Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-trainingCode0
Genetic Learning for Designing Sim-to-Real Data AugmentationsCode0
ANDA: A Novel Data Augmentation Technique Applied to Salient Object DetectionCode0
Practical X-ray Gastric Cancer Diagnostic Support Using Refined Stochastic Data Augmentation and Hard Boundary Box TrainingCode0
Semi-supervised Semantic Segmentation with Multi-Constraint Consistency LearningCode0
Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairingCode0
Improved Mixed-Example Data AugmentationCode0
Few-Shot Learning for Image Classification of Common FloraCode0
Policy Gradient-Driven Noise MaskCode0
Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic SegmentationCode0
Improving Fairness using Vision-Language Driven Image AugmentationCode0
Three things everyone should know to improve object retrievalCode0
Improving Performance of Federated Learning based Medical Image Analysis in Non-IID Settings using Image AugmentationCode0
Enhancing Autonomous Vehicle Perception in Adverse Weather through Image Augmentation during Semantic Segmentation TrainingCode0
Efficient Method for Categorize Animals in the WildCode0
Effective Dual-Region Augmentation for Reduced Reliance on Large Amounts of Labeled DataCode0
A Comparative Study on Efficiencies of Variants of Convolutional Neural Networks based on Image Classification TaskCode0
CochCeps-Augment: A Novel Self-Supervised Contrastive Learning Using Cochlear Cepstrum-based Masking for Speech Emotion RecognitionCode0
Domain Generalization with Fourier Transform and Soft ThresholdingCode0
Isometric Transformations for Image Augmentation in Mueller Matrix PolarimetryCode0
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?Code0
Discrete Wavelet Transform for Generative Adversarial Network to Identify Drivers Using Gyroscope and Accelerometer SensorsCode0
CIA: Controllable Image Augmentation Framework Based on Stable DiffusionCode0
Language-Driven Dual Style Mixing for Single-Domain Generalized Object DetectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified