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   Articles with "multilabel" as a keyword



MetaMBP: Few-Shot Multilabel Prediction of Bioactive Peptides Based on Deep Metric Meta-Learning

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recommendations! Published in 2025 at "Journal of chemical information and modeling"

DOI: 10.1021/acs.jcim.5c01309

Abstract: Bioactive peptides are highly specific and have low toxicity, making them a promising treatment option. There are many different types of bioactive peptides, while some types have limited samples (under 500). Methods that can handle… read more here.

Keywords: based deep; bioactive peptides; deep metric; metric meta ... See more keywords

Multilabel Feature Selection Using Mutual Information and ML-ReliefF for Multilabel Classification

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recommendations! Published in 2020 at "IEEE Access"

DOI: 10.1109/access.2020.3014916

Abstract: Recently, multilabel classification algorithms play an increasingly significant role in data mining and machine learning. However, some existing mutual information-based algorithms ignore the influence of the proportions of labels on the correlation degree between features… read more here.

Keywords: relieff; mutual information; multilabel classification; multilabel ... See more keywords

Federated Learning on Multilabel Evolving Data Streams

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

DOI: 10.1109/jiot.2025.3592954

Abstract: Multilabel classification in distributed evolving data stream environment presents significant challenges, including addressing distributed concept drifts and label dependencies. In this study, we introduce two novel solutions employing federated learning (FL) problem transformation techniques to… read more here.

Keywords: learning multilabel; evolving data; multilabel; federated learning ... See more keywords

Transformer-Driven Semantic Relation Inference for Multilabel Classification of High-Resolution Remote Sensing Images

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recommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2022.3145042

Abstract: It is hard to use a single label to describe an image for the complexity of remote sensing scenes. Thus, it is a more general and practical choice to use multilabel image classification for high-resolution… read more here.

Keywords: relation; semantic relation; multilabel; remote sensing ... See more keywords

Robust Online Multilabel Learning Under Dynamic Changes in Data Distribution With Labels

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recommendations! Published in 2020 at "IEEE Transactions on Cybernetics"

DOI: 10.1109/tcyb.2018.2869476

Abstract: In this paper, a robust online multilabel learning method dealing with dynamically changing multilabel data streams is proposed. The proposed method has three advantages: 1) higher accuracy due to a newly defined objective function based… read more here.

Keywords: multilabel; robust online; online multilabel; data distribution ... See more keywords

Multilabel Sample Augmentation-Based Hyperspectral Image Classification

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recommendations! Published in 2020 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2019.2962014

Abstract: The quantity and quality of training samples have a great influence on the performance of most hyperspectral image classification approaches. However, in a real scenario, manually annotating a large number of accurate training samples is… read more here.

Keywords: hyperspectral image; multilabel; training; image classification ... See more keywords

Degradation State Partition and Compound Fault Diagnosis of Rolling Bearing Based on Personalized Multilabel Learning

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recommendations! Published in 2021 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2021.3091504

Abstract: The prognostic and health management (PHM) of rolling bearings has been a popular research area. Since bearing fault is inevitable during degradation, how to improve the PHM performance based on both degradation states and fault… read more here.

Keywords: multilabel; multilabel learning; degradation; phm ... See more keywords

A Novel Interpretable Method Based on Dual-Level Attentional Deep Neural Network for Actual Multilabel Arrhythmia Detection

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recommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2021.3135330

Abstract: Arrhythmia accounts for more than 80% of sudden cardiac death, and its incidence rate has increased rapidly recently. Nowadays, many studies have applied artificial intelligence (AI) methods to arrhythmia detection. Deep learning approaches can improve… read more here.

Keywords: arrhythmia detection; arrhythmia; multilabel; dual level ... See more keywords

Online Passive-Aggressive Multilabel Classification Algorithms.

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

DOI: 10.1109/tnnls.2022.3164906

Abstract: Most existing multilabel classification methods are batch learning methods, which may suffer from expensive retraining costs when dealing with new incoming data. In order to overcome the drawbacks of batch learning, we develop a family… read more here.

Keywords: multilabel classification; multilabel; classification algorithms; online passive ... See more keywords

Partial Multilabel Learning Using Noise-Tolerant Broad Learning System With Label Enhancement and Dimensionality Reduction

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

DOI: 10.1109/tnnls.2024.3352285

Abstract: Partial multilabel learning (PML) addresses the issue of noisy supervision, which contains an overcomplete set of candidate labels for each instance with only a valid subset of training data. Using label enhancement techniques, researchers have… read more here.

Keywords: dimensionality reduction; space; label enhancement; multilabel ... See more keywords

L-VSM: Label-Driven View-Specific Fusion for Multiview Multilabel Classification

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

DOI: 10.1109/tnnls.2024.3390776

Abstract: In the task of multiview multilabel (MVML) classification, each instance is represented by several heterogeneous features and associated with multiple semantic labels. Existing MVML methods mainly focus on leveraging the shared subspace to comprehensively explore… read more here.

Keywords: view; label driven; instance; view specific ... See more keywords