Deep Residual Learning for Image Recognition
Actualmente diversas investigaciones se han enfocado en analizar a partir de videos de alta velocidad, características de las descargas eléctricas atmosféricas con el fin de adq...
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Actualmente diversas investigaciones se han enfocado en analizar a partir de videos de alta velocidad, características de las descargas eléctricas atmosféricas con el fin de adq...
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. On t...
A method is given for generating sets of special points in the Brillouin zone which provides an efficient means of integrating periodic functions of the wave vector. The integra...
se ha posicionado como un centro de referencia asistencial y académica, con la proyección de conformar clínicas o centros de excelencia.Para lograr este objetivo, es indispensab...
The global burden of cancer continues to increase largely because of the aging and growth of the world population alongside an increasing adoption of cancer-causing behaviors, p...
The CES-D scale is a short self-report scale designed to measure depressive symptomatology in the general population. The items of the scale are symptoms associated with depress...
In this important theoretical treatist, Jean Lave, anthropologist, and Etienne Wenger, computer scientist, push forward the notion of situated learning - that learning is fundam...
Instead of examining why organizations are dissimilar, this study explores why organizations tend to be increasingly and inevitably homogenous in their forms and practices. Orga...
Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the o...
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