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 201–250 of 308 papers

TitleStatusHype
Aug-ILA: More Transferable Intermediate Level Attacks with Augmented References—0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Augmenting Deep Learning Adaptation for Wearable Sensor Data through Combined Temporal-Frequency Image Encoding—0
Augmenting Vision-Based Human Pose Estimation with Rotation Matrix—0
Augment to Detect Anomalies with Continuous Labelling—0
Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention—0
Automated Segmentation and Analysis of Microscopy Images of Laser Powder Bed Fusion Melt Tracks—0
Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches—0
Automatic phantom test pattern classification through transfer learning with deep neural networks—0
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—0
Bayesian and Convolutional Networks for Hierarchical Morphological Classification of Galaxies—0
BGM: Background Mixup for X-ray Prohibited Items Detection—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation—0
Bridging the gap between AI and Healthcare sides: towards developing clinically relevant AI-powered diagnosis systems—0
Camera-based method for the detection of lifted truck axles using convolutional neural networks—0
Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN—0
CIMON: Towards High-quality Hash Codes—0
Interpretable CNN-Multilevel Attention Transformer for Rapid Recognition of Pneumonia from Chest X-Ray Images—0
Combining Noise-to-Image and Image-to-Image GANs: Brain MR Image Augmentation for Tumor Detection—0
Unified Framework for Histopathology Image Augmentation and Classification via Generative Models—0
Copy-Paste Image Augmentation with Poisson Image Editing for Ultrasound Instance Segmentation Learning—0
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations—0
Decision Support System for Detection and Classification of Skin Cancer using CNN—0
Deep Ensembling with Multimodal Image Fusion for Efficient Classification of Lung Cancer—0
Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review—0
Deep Learning Methods for Screening Pulmonary Tuberculosis Using Chest X-rays—0
deepTerra -- AI Land Classification Made Easy—0
Design of an Efficient Distracted Driver Detection System: Deep Learning Approaches—0
Design of Arabic Sign Language Recognition Model—0
Development of a Prototype Application for Rice Disease Detection Using Convolutional Neural Networks—0
Diagnosis of COVID-19 based on Chest Radiography—0
DiffClass: Diffusion-Based Class Incremental Learning—0
Diffusion Models for Robotic Manipulation: A Survey—0
Document Layout Analysis with Aesthetic-Guided Image Augmentation—0
DT/MARS-CycleGAN: Improved Object Detection for MARS Phenotyping Robot—0
Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model—0
DynASyn: Multi-Subject Personalization Enabling Dynamic Action Synthesis—0
Efficient Augmentation via Data Subsampling—0
Enhancing Document AI Data Generation Through Graph-Based Synthetic Layouts—0
Enhancing Pavement Crack Classification with Bidirectional Cascaded Neural Networks—0
Enhancing Transformer-Based Segmentation for Breast Cancer Diagnosis using Auto-Augmentation and Search Optimisation Techniques—0
Enhancing weed detection performance by means of GenAI-based image augmentation—0
Ensemble of Anchor-Free Models for Robust Bangla Document Layout Segmentation—0
Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification—0
Epicardial Adipose Tissue Segmentation from CT Images with A Semi-3D Neural Network—0
Evaluating GAN-Based Image Augmentation for Threat Detection in Large-Scale Xray Security Images—0
Evaluation and Comparison of Emotionally Evocative Image Augmentation Methods—0
Evolving Loss Functions for Specific Image Augmentation Techniques—0
Exemplar-Free Continual Transformer with Convolutions—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified