ORDAC adaptively corrects noisy ordinal labels via dynamic label distribution adjustments, yielding lower error and higher recall on noisy Adience and Diabetic Retinopathy benchmarks.
Objectlab: Automated diagnosis of mislabeled images in object detection data
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2025 2verdicts
UNVERDICTED 2representative citing papers
The paper introduces a safety framework for datasets in autonomous driving that uses the AI Data Flywheel and lifecycle processes to identify hazards and ensure compliance with ISO/PAS 8800.
citing papers explorer
-
Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels
ORDAC adaptively corrects noisy ordinal labels via dynamic label distribution adjustments, yielding lower error and higher recall on noisy Adience and Diabetic Retinopathy benchmarks.
-
Dataset Safety in Autonomous Driving: Requirements, Risks, and Assurance
The paper introduces a safety framework for datasets in autonomous driving that uses the AI Data Flywheel and lifecycle processes to identify hazards and ensure compliance with ISO/PAS 8800.