Semi-Supervised Self-Training Method Based on an Optimum-Path Forest
نویسندگان
چکیده
منابع مشابه
Supervised pattern classification based on optimum-path forest
We present an approach for supervised classification, which interprets a training set as a complete graph, identifies prototypes in all classes, and computes an optimum-path forest rooted at them. The class of a sample in a tree is assumed to be the same of its root. A test sample is classified by identifying which tree would contain it. We show how to improve performance from the errors on an ...
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Although one can find several pattern recognition techniques out there, there is still room for improvements and new approaches. In this book chapter, we revisited the Optimum-Path Forest (OPF) classifier, which has been evaluated over the last years in a number of applications that consider supervised, semi-supervised and unsupervised learning problems. We also presented a brief compilation of...
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We present a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), and describe one of its classifiers developed for the supervised learning case. This classifier does not require parameters and can handle some overlapping among multiple classes with arbitrary shapes. The method reduces the pattern recognition problem into the computation of an optimum-path forest in ...
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Since the creation of Generative Adversarial Networks (GANs), much work has been done to improve their training stability, their generated image quality, their range of application but nearly none of them explored their self-training potential. Self-training has been used before the advent of deep learning in order to allow training on limited labelled training data and has shown impressive res...
متن کاملA Self-Training Method for Semi-Supervised GANs
Since the creation of Generative Adversarial Networks (GANs), much work has been done to improve their training stability, their generated image quality, their range of application but nearly none of them explored their self-training potential. Self-training has been used before the advent of deep learning in order to allow training on limited labelled training data and has shown impressive res...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2903839