Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.
In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (C...
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 15 |
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| Autores principales: | , , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
10/26/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |