NL-MambaXCT combines masked image modeling pretraining with nested learning in a hybrid RegNet-Mamba encoder to reach 96.91% accuracy on Nomex honeycomb XCT defect classification using limited labels.
Journal of Big Data10(1), 46 (2023)
3 Pith papers cite this work, alongside 795 external citations. Polarity classification is still indexing.
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Resampling methods achieve near-perfect utility (TSTR 0.997) but fail privacy (DCR ~0), while VAEs balance 83.3% utility with full privacy protection for synthetic educational data.
Synthetic data generation in privacy-constrained medical domains shifts the engineering challenge from data availability to the elicitation, validation, and evolution of stakeholder-specific validity properties.
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NL-MambaXCT: Self-Supervised Nested-Learning Mamba for Nomex Honeycomb X-ray CT Defect Classification
NL-MambaXCT combines masked image modeling pretraining with nested learning in a hybrid RegNet-Mamba encoder to reach 96.91% accuracy on Nomex honeycomb XCT defect classification using limited labels.
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Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models
Resampling methods achieve near-perfect utility (TSTR 0.997) but fail privacy (DCR ~0), while VAEs balance 83.3% utility with full privacy protection for synthetic educational data.
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Property-Driven Synthetic Data Engineering for Data-Scarce Software Systems: Reflections from the Breast Cancer Domain
Synthetic data generation in privacy-constrained medical domains shifts the engineering challenge from data availability to the elicitation, validation, and evolution of stakeholder-specific validity properties.