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A semi-supervised framework for concept-based hierarchical document clustering
Text clustering is used in various applications of text analysis. In the clustering process, the employed document representation method has a...
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End-to-end semi-supervised approach with modulated object queries for table detection in documents
Table detection, a pivotal task in document analysis, aims to precisely recognize and locate tables within document images. Although deep learning...
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Fairness in graph-based semi-supervised learning
Machine learning is widely deployed in society, unleashing its power in a wide range of applications owing to the advent of big data. One emerging...
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Semi-supervised diagnosis of wind-turbine gearbox misalignment and imbalance faults
AbstractBoth wear-induced bearing failure and misalignment of the powertrain between the rotor and the electrical generator are common failure modes...
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Sequential semi-supervised active learning model in extremely low training set (SSSAL)
With the rapid development of computing and multimedia technology, the volume of web traffic data, social networks, sensors and other types of...
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Towards improving the performance of traffic sign recognition using support vector machine based deep learning model
Nowadays autonomous vehicles are evolving due to the advancements in cutting edge technologies. In order to recognize the traffic signatures with...
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Semi-supervised labeling: a proposed methodology for labeling the twitter datasets
Twitter has nowadays become a trending microblogging and social media platform for news and discussions. Since the dramatic increase in its platform...
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A least squares twin support vector machine method with uncertain data
Twin support vector machine (TWSVM) learns two nonparallel hyperplanes for binary class classification problems. It assumes that the training data...
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Joint Label Propagation, Graph and Latent Subspace Estimation for Semi-supervised Classification
Obtaining labeled images and samples is a very expensive process and can require intensive labor. At the same time, there are often not enough...
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A systematic review for class-imbalance in semi-supervised learning
This review aims to examine the state of the art of semi-supervised learning (SSL) techniques for addressing class imbalanced data. Class imbalance...
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Multi-view Representation Induced Kernel Ensemble Support Vector Machine
This paper proposes a multi-view representation kernel ensemble Support Vector Machine. Unlike the conventional multiple kernel learning techniques...
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Machine Learning-Based DDoS Attack Detection Using Support Vector Machine
Intrusion and cyber-attacks are increasing drastically in today’s digital era. The cost involved in cyber security increased 600% during the COVID-19...
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Semi-supervised adversarial discriminative domain adaptation
Domain adaptation is a potential method to train a powerful deep neural network across various datasets. More precisely, domain adaptation methods...
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Image classification with consistency-regularized bad semi-supervised generative adversarial networks: a visual data analysis and synthesis
Semi-supervised learning, which entails training a model with manually labeled images and pseudo-labels for unlabeled images, has garnered...
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Multi-scale constraints and perturbation consistency for semi-supervised sonar image segmentation
Emerging semi-supervised learning methods have enabled great progress in segmentation tasks. However, popular semi-supervised segmentation models use...
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Gaussian transformation enhanced semi-supervised learning for sleep stage classification
Sleep disorders are significant health concerns affecting a large population. Related clinical studies face the deficiency in sleep data and...
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Semi-supervised attack detection in industrial control systems with deviation networks and feature selection
With the rapid development of Industry 4.0, the importance of cyber security for industrial control systems has become increasingly prominent. The...
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Segmentation technique for the detection of Micro cracks in solar cell using support vector machine
Micro cracks in solar cells lower the overall performance of the solar panel. These cracks result from poor handling during transportation,...
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Support Vector Machine Classification
Support vector machine (SVM) has been a popular technique in data analytics. Shi et al. [1] has reported some SVM algorithms. They vary from...
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Semi-supervised classifier with projection graph embedding for motor imagery electroencephalogram recognition
Brain computer interface (BCI) based on motor imagery (MI) provides a communication channel between the brain and a computer or other communication...
