Method for classifying images in databases through deep convolutional networks
Artículo de revista
2020
Corporación Universidad de la Costa
Since 2006, deep structured learning, or more commonly called deep learning or hierarchical learning, has become a new area of research in machine learning. In recent years, techniques developed from deep learning research have impacted on a wide range of information and particularly image processing studies, within traditional and new fields, including key aspects of machine learning and artificial intelligence. This paper proposes an alternative scheme for training data management in CNNs, consisting of selective-adaptive data sampling. By means of experiments with the CIFAR10 database for image classification.
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Method for classifying images in databases through deep convolutional networks.pdf
Título: Method for classifying images in databases through deep convolutional networks.pdf
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Título: Method for classifying images in databases through deep convolutional networks.pdf
Tamaño: 1.505Mb
PDFLEER EN FLIP
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