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Rank-based self-training for graph convolutional networks
(2021-03-01)
Graph Convolutional Networks (GCNs) have been established as a fundamental approach for representation learning on graphs, based on convolution operations on non-Euclidean domain, defined by graph-structured data. GCNs and ...
Application of training periodization models by elite judo coaches
(Int Scientific Literature, Inc, 2017-05-22)
Background and Study Aim: Periodization and structured training models are prominent concepts in the field of sports science. Nevertheless, the structure of the training of Brazilian elite judo athletes and the periodization ...
Application of training periodization models by elite judo coaches
(2017-01-01)
Background and Study Aim: Periodization and structured training models are prominent concepts in the field of sports science. Nevertheless, the structure of the training of Brazilian elite judo athletes and the periodization ...
Semi-supervised learning with convolutional neural networks for UAV images automatic recognition
(Elsevier B.V., 2019-09-01)
The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
Semi-supervised learning with connectivity-driven convolutional neural networks
(2019-12-01)
The annotation of large datasets is an issue whose challenge increases as the number of labeled samples available to train the classifier reduces in comparison to the amount of unlabeled data. In this context, semi-supervised ...
Velocity loss thresholds reliably control kinetic and kinematic outputs during free weight resistance training
(International Journal of Environmental Research and Public Health, 2021)
Hierarchical clustering and stochastic distance for indirect semi-supervised remote sensing image classification
(Springer, 2019-03-01)
Usually, image classification methods have supervised or unsupervised learning paradigms. While unsupervised methods do not need training data, the meanings behind the classified elements are not explicitly know. Conversely, ...
A REFLECTIVE APPROACH FOR TEACHING SEMI-AUTOMATIC TRANSLATION PRACTICE IN TRANSLATOR TRAINING PROGRAMS
(Univ Federal Santa Catarina, Nucleo Traducao, 2019-05-01)
Translation memory systems have been promoting definitive changes in the development and contracting criteria of translations of texts in electronic format. With the purpose of examining the influence of the use of these ...
Improving semi-supervised learning through optimum connectivity
(Elsevier B.V., 2016-12-01)
The annotation of large data sets by a classifier is a problem whose challenge increases as the number of labeled samples used to train the classifier reduces in comparison to the number of unlabeled samples. In this ...
Case studies: teaching mathematics in a school of management
(Univ Pedagogica & Tecnologica Colombia, 2020-01-01)
Our aim is to show the organizational process of teaching of three math teachers in a management university institution, based on the collective creation of case studies. The dialectical method provided elements to understand ...