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 151–200 of 308 papers

TitleStatusHype
Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications—0
Semantic-Guided Generative Image Augmentation Method with Diffusion Models for Image Classification—0
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding—0
Semi-supervised object detection based on single-stage detector for thighbone fracture localization—0
Semmeldetector: Application of Machine Learning in Commercial Bakeries—0
SGIA: Enhancing Fine-Grained Visual Classification with Sequence Generative Image Augmentation—0
Exploring Simple, High Quality Out-of-Distribution Detection with L2 Normalization—0
Slot Based Image Augmentation System for Object Detection—0
Spatially Visual Perception for End-to-End Robotic Learning—0
Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images—0
Synthesizing Diverse Lung Nodules Wherever Massively: 3D Multi-Conditional GAN-based CT Image Augmentation for Object Detection—0
Synthetic Image Augmentation for Damage Region Segmentation using Conditional GAN with Structure Edge—0
Synthetic Image Augmentation for Improved Classification using Generative Adversarial Networks—0
Tab2Visual: Overcoming Limited Data in Tabular Data Classification Using Deep Learning with Visual Representations—0
Temperate Fish Detection and Classification: a Deep Learning based Approach—0
Time Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network—0
Toward Fault Detection in Industrial Welding Processes with Deep Learning and Data Augmentation—0
Towards Composable Distributions of Latent Space Augmentations—0
Leveraging Image Augmentation for Object Manipulation: Towards Interpretable Controllability in Object-Centric Learning—0
Towards Performance Improvement in Indian Sign Language Recognition—0
A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms—0
USING OBJECT-FOCUSED IMAGES AS AN IMAGE AUGMENTATION TECHNIQUE TO IMPROVE THE ACCURACY OF IMAGE-CLASSIFICATION MODELS WHEN VERY LIMITED DATA SETS ARE AVAILABLE—0
River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index—0
Wind Turbine Blade Surface Damage Detection based on Aerial Imagery and VGG16-RCNN Framework—0
Worsening Perception: Real-time Degradation of Autonomous Vehicle Perception Performance for Simulation of Adverse Weather Conditions—0
Yelp Food Identification via Image Feature Extraction and Classification—0
Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation—0
Automated Detection of Salvin's Albatrosses: Improving Deep Learning Tools for Aerial Wildlife Surveys—0
3D Hierarchical Refinement and Augmentation for Unsupervised Learning of Depth and Pose from Monocular Video—0
A CNN toolbox for skin cancer classification—0
A Comprehensive Survey of Image Augmentation Techniques for Deep Learning—0
A convolutional neural network of low complexity for tumor anomaly detection—0
A Data-Driven Approach to Improve 3D Head-Pose Estimation—0
Advances in Diffusion Models for Image Data Augmentation: A Review of Methods, Models, Evaluation Metrics and Future Research Directions—0
A framework for river connectivity classification using temporal image processing and attention based neural networks—0
A Methodology to Identify Cognition Gaps in Visual Recognition Applications Based on Convolutional Neural Networks—0
Anomaly Detection Using Computer Vision: A Comparative Analysis of Class Distinction and Performance Metrics—0
A novel action recognition system for smart monitoring of elderly people using Action Pattern Image and Series CNN with transfer learning—0
A Novel Breast Ultrasound Image Augmentation Method Using Advanced Neural Style Transfer: An Efficient and Explainable Approach—0
A Probabilistic Model for Discriminative and Neuro-Symbolic Semi-Supervised Learning—0
A Residual Encoder-Decoder Network for Segmentation of Retinal Image-Based Exudates in Diabetic Retinopathy Screening—0
A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks—0
A Tale of Color Variants: Representation and Self-Supervised Learning in Fashion E-Commerce—0
A Technical Report for ICCV 2021 VIPriors Re-identification Challenge—0
A Technical Report for VIPriors Image Classification Challenge—0
Attention-Driven Lightweight Model for Pigmented Skin Lesion Detection—0
Attention W-Net: Improved Skip Connections for better Representations—0
AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Image—0
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
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AugstaticBalanced Accuracy0—Unverified