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...

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Detalles Bibliográficos
Autores principales: Zhong, Bineng, Pan, Shengnan, Zhang, Hongbo, Wang, Tian, Du, Jixiang, Chen, Duansheng, Cao, Liujuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101405/
https://www.ncbi.nlm.nih.gov/pubmed/27847827
http://dx.doi.org/10.1155/2016/9406259

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101405/
https://www.ncbi.nlm.nih.gov/pubmed/27847827
http://dx.doi.org/10.1155/2016/9406259

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