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Neural connectomics challenge

Battaglia, Demian.

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Neural connectomics challenge

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Neural connectomics challenge/ edited by Demian Battaglia ... [et al.].
其他作者:	Battaglia, Demian.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	x, 117 p. :ill., digital ;24 cm.
內容註:	First Connectomics Challenge: From Imaging to Connectivity -- Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging -- Supervised Neural Network Structure Recovery -- Signal Correlation Prediction Using Convolutional Neural Networks -- Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization -- Neural Connectivity Reconstruction from Calcium Imaging Signal using Random Forest with Topological Features -- Efficient Combination of Pairwise Feature Networks -- Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model -- SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data -- Supplemental Information.
Contained By:	Springer eBooks
標題:	Computational neuroscience. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-53070-3
ISBN:	9783319530703

Neural connectomics challenge
Neural connectomics challenge[electronic resource] /edited by Demian Battaglia ... [et al.]. - Cham :Springer International Publishing :2017. - x, 117 p. :ill., digital ;24 cm. - The Springer series on challenges in machine learning,2520-131X. - Springer series on challenges in machine learning..

First Connectomics Challenge: From Imaging to Connectivity -- Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging -- Supervised Neural Network Structure Recovery -- Signal Correlation Prediction Using Convolutional Neural Networks -- Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization -- Neural Connectivity Reconstruction from Calcium Imaging Signal using Random Forest with Topological Features -- Efficient Combination of Pairwise Feature Networks -- Predicting Spiking Activities in DLS Neurons with Linear-Nonlinear-Poisson Model -- SuperSlicing Frame Restoration for Anisotropic ssTEM and Video Data -- Supplemental Information.

ISBN: 9783319530703

Standard No.: 10.1007/978-3-319-53070-3doiSubjects--Topical Terms:

610819
Computational neuroscience.

LC Class. No.: QP357.5

Dewey Class. No.: 612.8

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