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SETRED: Self-training with Editing
2005Self-training is a semi-supervised learning algorithm in which a learner keeps on labeling unlabeled examples and retraining itself on an enlarged labeled training set. Since the self-training process may erroneously label some unlabeled examples, sometimes the learned hypothesis does not perform well.
Ming Li 0005, Zhi-Hua Zhou
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Self-Training System of Calligraphy Brushwork
Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017In this paper, we describe a self-training system of brushwork of calligraphy. For writing a well-shaped character, the brushwork should be controlled properly. In the developed system, the motion of the student's brush is measured by Leapmotion sensor, and if the handwriting is not proper, the student's wrist is stimulated by a pressure presentation ...
Ami Morikawa +3 more
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Self-trained automated parking system
ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004., 2005This paper presents part of the research work carried out at the Centre for Computational Intelligence at NTU to develop novel technologies for the routing, navigation, and control of intelligent cars. One objective is to endow the cars with the ability to autonomously drive on various types of roads and realize manoeuvres such as reverse and parallel ...
Richard Jayadi Oentaryo, Michel Pasquier
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A soft-labeled self-training approach
2016 23rd International Conference on Pattern Recognition (ICPR), 2016Semi-supervised classification methods try to improve a supervised learned classifier with the help of unlabeled data. In many cases one assumes a certain structure on the data, as for example the manifold assumption, the smoothness assumption or the cluster assumption.
Alexander Mey, Marco Loog
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An Improved Self-Training for Face Recognition
2013 Seventh International Conference on Image and Graphics, 2013Face recognition has attracted considerable concerns in recent years. In practical applications, there are generally a small amount of labeled face images and a lot of unlabeled ones can be available. In this paper, we introduce a semi-supervised face recognition method where semi-supervised LDA (SDA) and Affinity Propagation (AP) are integrated into ...
Haitao Gan +4 more
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Self-training with adaptive regularization for S3VM
2017 International Joint Conference on Neural Networks (IJCNN), 2017The Semi-Supervised Support Vector Machine (S3VM) solves a non-convex, Mixed-Integer Program (MIP). Due to difficulty in solving the problem, convex approximations have typically been used. However, existing approaches suffer from poor scalability and struggle on certain datasets, compared to graph based counterparts.
Edward Cheung, Yuying Li 0001
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Self-training for Cell Segmentation and Counting
2019Learning semantic segmentation and object counting often need a large amount of training data while manual labeling is expensive. The goal of this paper is to train such networks on a small set of annotations. We propose an Expectation Maximization(EM)-like self-training method that first trains a model on a small amount of labeled data and adds ...
Junliang Luo +4 more
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An incremental self-trained ensemble algorithm
2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2018Incremental learning has boosted the speed of Data Mining algorithms without sacrificing much, or sometimes none, predictive accuracy. Instead, by saving computational resources, combination of such kind of algorithms with iterative procedures that improve the learned hypothesis utilizing vast amounts of available unlabeled data could be achieved ...
Stamatis Karlos +4 more
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2010
You have to make the five elementary pictures of the program and paste them in the book on the places reserved for that purpose. Take part in the play and you will be pleasantly surprised at the result.
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You have to make the five elementary pictures of the program and paste them in the book on the places reserved for that purpose. Take part in the play and you will be pleasantly surprised at the result.
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Yoga Posture Recognition for Self-training
2014Self-training plays an important role in sports exercise, but improper training postures can cause serious harm to muscles and ligaments of the body. Hence, more and more researchers are devoted into the development of computer-assisted self-training systems for sports exercise.
Hua-Tsung Chen +5 more
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