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Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning

, , , and . International Conference on Pattern Recognition (ICPR), page 9483--9490. IEEE, (2021)
DOI: 10.1109/icpr48806.2021.9411918

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Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges., , , , , , , and . CoRR, (2019)Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning, , , and . arXiv e-prints, (2020)Trust Your Model: Iterative Label Improvement and Robust Training by Confidence Based Filtering and Dataset Partitioning., , , and . CoRR, (2020)Pass Phrase Based Speaker Recognition for Authentication., , and . BIOSIG, volume P-31 of LNI, page 71-80. GI, (2003)Effectiveness in open-set speaker identification., , and . ICCST, page 1-6. IEEE, (2014)Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning, , , and . International Conference on Pattern Recognition (ICPR), page 9483--9490. IEEE, (2021)Estimating Labeling Quality with Deep Object Detectors., , and . IV, page 33-38. IEEE, (2019)Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges., , , , , , , and . IEEE Trans. Intell. Transp. Syst., 22 (3): 1341-1360 (2021)Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning., , , and . ICPR, page 9483-9490. IEEE, (2020)Effectiveness in the Realisation of Speaker Authentication., , , and . ICCST, page 1-5. IEEE, (2019)