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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 308 papers

TitleStatusHype
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—0
A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning—0
Automatic phantom test pattern classification through transfer learning with deep neural networks—0
Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches—0
Exemplar-Free Continual Transformer with Convolutions—0
Automated Segmentation and Analysis of Microscopy Images of Laser Powder Bed Fusion Melt Tracks—0
Anomaly Detection Using Computer Vision: A Comparative Analysis of Class Distinction and Performance Metrics—0
Evaluation and Comparison of Emotionally Evocative Image Augmentation Methods—0
Diffusion Models for Robotic Manipulation: A Survey—0
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video—0
Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images—0
Evolving Loss Functions for Specific Image Augmentation Techniques—0
Explanatory Analysis and Rectification of the Pitfalls in COVID-19 Datasets—0
Exploring Temporally Dynamic Data Augmentation for Video Recognition—0
Diagnosis of COVID-19 based on Chest Radiography—0
Development of a Prototype Application for Rice Disease Detection Using Convolutional Neural Networks—0
Augment to Detect Anomalies with Continuous Labelling—0
Advances in Diffusion Models for Image Data Augmentation: A Review of Methods, Models, Evaluation Metrics and Future Research Directions—0
Design of Arabic Sign Language Recognition Model—0
DiffClass: Diffusion-Based Class Incremental Learning—0
Design of an Efficient Distracted Driver Detection System: Deep Learning Approaches—0
Augmenting Vision-Based Human Pose Estimation with Rotation Matrix—0
deepTerra -- AI Land Classification Made Easy—0
Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention—0
Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified