SOTAVerified

Dataset Generation

The task involves enhancing the training of target application (e.g. autonomous driving systems) by generating datasets of diverse and critical elements (e.g. traffic scenarios). Traditional methods rely on expensive and limited datasets, which often fail to capture rare but essential situations that can pose risks during testing.

Papers

Showing 291300 of 308 papers

TitleStatusHype
Synthetic dataset generation for object-to-model deep learning in industrial applicationsCode0
Learning to Propagate for Graph Meta-LearningCode0
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative ModelsCode0
Methodology for the Automated Metadata-Based Classification of Incriminating Digital Forensic Artefacts0
Selection of Waveform Parameters Using Machine Learning for 5G and Beyond0
Rethinking Table Recognition using Graph Neural NetworksCode0
LeagueAI: Improving object detector performance and flexibility through automatically generated training data and domain randomizationCode0
Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classificationCode0
Boundary Aware Multi-Focus Image Fusion Using Deep Neural Network0
A Seed-Augment-Train Framework for Universal Digit Classification0
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