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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Dades bibliogràfiques
Publicat a:Biomed Res Int
Autors principals: Zhong, Bineng, Pan, Shengnan, Zhang, Hongbo, Wang, Tian, Du, Jixiang, Chen, Duansheng, Cao, Liujuan
Format: Artigo
Idioma:Inglês
Publicat: Hindawi Publishing Corporation 2016
Matèries:
Research Article
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC5101405/
https://ncbi.nlm.nih.gov/pubmed/27847827
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2016/9406259
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