Results 11 to 20 of about 338,614 (301)
A survey of large-scale graph-based semi-supervised classification algorithms
International Journal of Cognitive Computing in Engineering, 2022 Semi-supervised learning is an effective method to study how to use both labeled data and unlabeled data to improve the performance of the classifier, which has become the hot field of machine learning in recent years.
Yunsheng Song, Jing Zhang, Chao Zhang
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Tracking-based semi-supervised learning [PDF]
The International Journal of Robotics Research, 2011 We consider a semi-supervised approach to the problem of track classification in dense three-dimensional range data. This problem involves the classification of objects that have been segmented and tracked without the use of a class-specific tracker. This paper is an extended version of our previous work.
Alex Teichman, Sebastian Thrun
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Semi-supervised Learning Method Based on Automated Mixed Sample Data Augmentation Techniques [PDF]
Jisuanji kexue, 2022 Consistency-based semi-supervised learning methods typically use simple data augmentation methods to achieve consistent predictions for both original inputs and perturbed inputs.The effectiveness of this approach is difficult to be guaranteed when the ...
XU Hua-jie, CHEN Yu, YANG Yang, QIN Yuan-zhuo
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Meta-Semi: A Meta-Learning Approach for Semi-Supervised Learning
CAAI Artificial Intelligence Research, 2022 Deep learning based semi-supervised learning (SSL) algorithms have led to promising results in recent years. However, they tend to introduce multiple tunable hyper-parameters, making them less practical in real SSL scenarios where the labeled data is ...
Yulin Wang +5 more
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International Journal of Applied Mathematics and Computer Science, 2023 Acoustic features of speech are promising as objective markers for mental health monitoring. Specialized smartphone apps can gather such acoustic data without disrupting the daily activities of patients.
Casalino Gabriella +6 more
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Information, 2021 Smart grids integrate advanced information and communication technologies (ICTs) into traditional power grids for more efficient and resilient power delivery and management, but also introduce new security vulnerabilities that can be exploited by ...
Ruobin Qi +3 more
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Pseudo-Labeling Optimization Based Ensemble Semi-Supervised Soft Sensor in the Process Industry
Sensors, 2021 Nowadays, soft sensor techniques have become promising solutions for enabling real-time estimation of difficult-to-measure quality variables in industrial processes.
Youwei Li +4 more
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Semi-Supervised Learning with Scarce Annotations [PDF]
, 2019 While semi-supervised learning (SSL) algorithms provide an efficient way to make use of both labelled and unlabelled data, they generally struggle when the number of annotated samples is very small.
Ehrhardt, Sebastien +4 more
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Semi‐supervised uncorrelated dictionary learning for colour face recognition
IET Computer Vision, 2020 Colour images are increasingly used in the fields of computer vision, pattern recognition and machine learning, since they can provide more identifiable information than greyscale images. Thus, colour face recognition has attracted accumulating attention.
Qian Liu +4 more
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Semi-supervised Learning Algorithm Based on Maximum Margin and Manifold Hypothesis [PDF]
Jisuanji kexueSemi-supervised learning is a weakly supervised learning pattern between supervised learning and unsupervised lear-ning.It combines a small number of labeled instances with a large number of unlabeled instances to build a model during the process of ...
DAI Wei, CHAI Jing, LIU Yajiao
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