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   Articles with "low confidence" as a keyword



Augmented Data Low Confidence (ADLC): A Confidence-Driven Data Augmentation Framework With Ensemble Optimization for Enhanced Machine Learning Performance

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3636729

Abstract: The application of machine learning in data-driven solutions has matured, yet efforts continue to improve predictive accuracy. This study presents a comprehensive approach that begins with data preprocessing, including the removal of invalid values, duplicate… read more here.

Keywords: low confidence; machine learning; performance; confidence ... See more keywords

MD-TLCF: Miner Distance Detection Based on Trajectory-Based Low-Confidence Filter

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recommendations! Published in 2024 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2024.3412212

Abstract: The confidence level of the detection result generally indicates the reliability of the detected object. However, in underground coal mines with low light intensity and uneven light distribution, the confidence level of detection results is… read more here.

Keywords: detection; miner; distance; low confidence ... See more keywords

MutexMatch: Semi-supervised Learning with Mutex-based Consistency Regularization

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recommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3228380

Abstract: The core issue in semi-supervised learning (SSL) lies in how to effectively leverage unlabeled data, whereas most existing methods tend to put a great emphasis on the utilization of high-confidence samples yet seldom fully explore… read more here.

Keywords: consistency; confidence; semi supervised; supervised learning ... See more keywords

Uncertainty-Aware Semi-Supervised Method for Pectoral Muscle Segmentation

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recommendations! Published in 2025 at "Bioengineering"

DOI: 10.3390/bioengineering12010036

Abstract: The consistency regularization method is a widely used semi-supervised method that uses regularization terms constructed from unlabeled data to improve model performance. Poor-quality target predictions in regularization terms produce noisy gradient flows during training, resulting… read more here.

Keywords: low confidence; semi supervised; target predictions; confidence ... See more keywords