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   Articles with "ood" as a keyword



MLR-OOD: a Markov chain based Likelihood Ratio method for Out-Of-Distribution detection of genomic sequences.

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recommendations! Published in 2022 at "Journal of molecular biology"

DOI: 10.1016/j.jmb.2022.167586

Abstract: Machine learning or deep learning models have been widely used for taxonomic classification of metagenomic sequences and many studies reported high classification accuracy. Such models are usually trained based on sequences in several training classes… read more here.

Keywords: likelihood ratio; ood; markov chain; mlr ood ... See more keywords

A noise-robust classification method for cryo-ET subtomograms with out-of-distribution detection

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recommendations! Published in 2025 at "Bioinformatics"

DOI: 10.1093/bioinformatics/btaf274

Abstract: Abstract Motivation Cryogenic electron tomography (cryo-ET) enables high-resolution 3D reconstruction of biological samples, with accurate subtomogram classification critical for structural analysis. However, current subtomogram classification methods often struggle with out-of-distribution (OOD) data issue, causing misclassification… read more here.

Keywords: classification; detection; distribution; ood ... See more keywords

Out-of-Distribution Detection Based on Multiple Metrics Fusion of Network Hidden Features

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recommendations! Published in 2024 at "IEEE Access"

DOI: 10.1109/access.2024.3471693

Abstract: Traditional pattern recognition models achieve excellent classification performance. However, when out-of-distribution (OOD) samples, which are outside the training distribution of in-distribution (ID) data, are input into the model, the model often assigns excessively high confidence.… read more here.

Keywords: detection; distribution; ood; fusion ... See more keywords

On Risk Assessment for Out-of-Distribution Detection

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3533201

Abstract: This paper challenges the conventional approach treating of out-of-distribution (OOD) risk as uniform and aimed at reducing OOD risk on average. We argue that managing OOD risk on average fails to account for the potential… read more here.

Keywords: detection; distribution; ood; risk ... See more keywords

Deep Neural Forest for Out-of-Distribution Detection of Skin Lesion Images

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recommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"

DOI: 10.1109/jbhi.2022.3171582

Abstract: Deep learning methods have shown outstanding potential in dermatology for skin lesion detection and identification. However, they usually require annotations beforehand and can only classify lesion classes seen in the training set. Moreover, large-scale, open-sourced… read more here.

Keywords: ood; skin lesion; detection; lesion ... See more keywords
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Robust Cough Detection with Out-of-Distribution Detection.

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recommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"

DOI: 10.1109/jbhi.2023.3264783

Abstract: Cough is an important defense mechanism of the respiratory system and is also a symptom of lung diseases, such as asthma. Acoustic cough detection collected by portable recording devices is a convenient way to track… read more here.

Keywords: robust cough; ood; cough detection; detection ... See more keywords

Energy-Propagation Graph Neural Networks for Enhanced Out-of-Distribution Fault Analysis in Intelligent Construction Machinery Systems

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recommendations! Published in 2025 at "IEEE Internet of Things Journal"

DOI: 10.1109/jiot.2024.3463718

Abstract: In intelligent fault diagnosis for construction machinery, robust and precise detection of out-of-distribution (OOD) data is crucial for enhancing operational efficiency and reducing downtime. This article introduces the energy-driven graph neural OOD (EGN-OOD) detector, a… read more here.

Keywords: energy; construction machinery; ood; graph neural ... See more keywords

Mitigating SAR Out-of-Distribution Overconfidence Based on Evidential Uncertainty

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recommendations! Published in 2024 at "IEEE Geoscience and Remote Sensing Letters"

DOI: 10.1109/lgrs.2024.3443330

Abstract: Synthetic aperture radar (SAR) automatic target recognition (ATR) is extensively applied in both military and civilian sectors. Nevertheless, test and training data distribution may differ in the open world. Therefore, SAR out-of-distribution (OOD) detection is… read more here.

Keywords: sar distribution; distribution; ood; ood detection ... See more keywords

ReSmooth: Detecting and Utilizing OOD Samples when Training with Data Augmentation

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

DOI: 10.1109/tnnls.2022.3222044

Abstract: Data augmentation (DA) is a widely used technique for enhancing the training of deep neural networks. Recent DA techniques which achieve state-of-the-art performance always meet the need for diversity in augmented training samples. However, an… read more here.

Keywords: ood; resmooth detecting; data augmentation; ood samples ... See more keywords

Gently Sloped and Extended Classification Margin for Overconfidence Relaxation of Out-of-Distribution Samples

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recommendations! Published in 2024 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2024.3496473

Abstract: Recently, machine learning models are expected to be capable of detecting out-of-distribution (OOD) samples for safe use. However, the existing OOD detection methods have limitations. Post hoc calibration techniques used for OOD detection during the… read more here.

Keywords: distribution; ood; gently sloped; classification margin ... See more keywords

MOOD: Leveraging Out-of-Distribution Data to Enhance Imbalanced Semi-Supervised Learning

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recommendations! Published in 2025 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2025.3573963

Abstract: The imbalanced semi-supervised learning (SSL) has emerged as a critical research area due to the prevalence of class imbalanced and partially labeled data in real-world scenarios. As the requirement for data volume increases, naturally collected… read more here.

Keywords: ood data; distribution; ood; supervised learning ... See more keywords