Latest Articles for Data Augmentation

A new method improves how streaming services recommend films based on genres.

A new system aids dermatologists in identifying skin patterns using machine learning.

Researchers develop robots that learn table tennis through human-like demonstrations.

This study shows how new methods enhance knee OA severity classification.

This article discusses the importance and obstacles in fact verification systems.

Mixup techniques enhance machine learning accuracy in physiological time series data analysis.

New technique improves diversity of indoor panoramic image datasets.

LesionMix improves data augmentation for better detection of lesions in medical images.

A new method enhances target recognition in SAR images with less training data.

Research shows how simplifying data use improves self-driving vehicle performance.

Learn how LP-CLIP enhances the robustness of multi-modal models like CLIP.

This article discusses new methods for improving navigation near asteroids.

Improving methods for detecting solar panels through remote sensing technology.

This article discusses how LLMs can create new datasets for reading comprehension tasks.

New method generates counterfactual examples for better model evaluation and training.

Order-preserving Consistency Regularization improves model performance in diverse situations.

Examining social bias in machine learning, focusing on language, vision, and vision-language models.

Strategies to enhance interpretability in AI systems for better understanding.

Explore Gibbs sampling and data augmentation in statistical modeling.

A new method improves audio tagging performance and efficiency.

FDLS streamlines the creation of realistic digital character animations using deep learning.

A new model improves recognition of rare categories in imbalanced datasets.

Study shows Supervised Contrastive Learning enhances model performance across varied datasets.

A new model improves image recognition by adapting to transformations uniquely.

RLLTE provides a flexible framework for developing and improving reinforcement learning applications.

New approach enhances deep learning models for reliable medical image segmentation.

New techniques enhance model performance using limited labeled data.

Proper data separation enhances lung cancer detection accuracy using deep learning.

A new method enhances positive sample generation in self-supervised learning.

Exploring the significance of feature normalization in non-contrastive learning dynamics.

BOD simplifies data analysis by involving users in ranking important variables.

A new lightweight model improves pitch estimation using self-supervised learning techniques.

Research improves force prediction in robotic surgery using visual data and machine learning.

A deep learning method enhances kidney problem detection in medical imaging.

Examining fairness and accuracy in detecting vulnerable road users by autonomous vehicles.

NAG2G enhances the process of predicting reactants for compound synthesis.

A new approach enhances NLP models against adversarial attacks through targeted paraphrasing.

A new AI framework improves eye disease detection through enhanced imaging techniques.

New methods aim to enhance pneumonia diagnosis in children's lung health.

FrameFlow propels protein design by enhancing scaffold diversity and functionality.