Probabilistic inference of binary Markov random fields in spiking neural networks through mean-field approximation

Neural Networks ◽

10.1016/j.neunet.2020.03.003 ◽

2020 ◽

Vol 126 ◽

pp. 42-51 ◽

Author(s):

Yajing Zheng ◽

Shanshan Jia ◽

Zhaofei Yu ◽

Tiejun Huang ◽

Jian K. Liu ◽

...

Keyword(s):

Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Probabilistic Inference ◽

Field Approximation ◽

Spiking Neural Networks ◽

Mean Field Approximation ◽

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Improved object segmentation using Markov random fields, artificial neural networks, and parallel processing techniques

10.1117/12.280826 ◽

1997 ◽

Author(s):

Stephen B. Foulkes ◽

David M. Booth

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Parallel Processing ◽

Random Fields ◽

Markov Random Fields ◽

Object Segmentation ◽

Markov Random ◽

Artificial Neural ◽

Processing Techniques

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Classification of multitemporal SAR images using convolutional neural networks and Markov random fields

2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) ◽

10.1109/igarss.2017.8127432 ◽

2017 ◽

Author(s):

Carolyne Danilla ◽

Claudio Persello ◽

Valentyn Tolpekin ◽

John Ray Bergado

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

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The Mean Field Theory In EM Procedures For Markov Random Fields

Proceedings of the Seventh Workshop on Multidimensional Signal Processing ◽

10.1109/mdsp.1991.639423 ◽

2005 ◽

Author(s):

Jun Zhang

Keyword(s):

Field Theory ◽

Random Fields ◽

Markov Random Fields ◽

Mean Field Theory ◽

Markov Random ◽

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Combining Monte Carlo and Mean-Field-Like Methods for Inference in Hidden Markov Random Fields

IEEE Transactions on Image Processing ◽

10.1109/tip.2006.891045 ◽

2007 ◽

Vol 16 (3) ◽

pp. 824-837 ◽

Author(s):

Florence Forbes ◽

Gersende Fort

Keyword(s):

Monte Carlo ◽

Random Fields ◽

Markov Random Fields ◽

Hidden Markov ◽

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Mean field approximation using compound Gauss-Markov random field for edge detection and image restoration

10.1109/icassp.1990.115992 ◽

2002 ◽

Author(s):

J. Zerubia ◽

R. Challappa

Keyword(s):

Edge Detection ◽

Random Field ◽

Image Restoration ◽

Markov Random Field ◽

Field Approximation ◽

Mean Field Approximation ◽

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Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) ◽

10.1109/cvpr.2016.272 ◽

2016 ◽

Author(s):

Chuan Li ◽

Michael Wand

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Image Synthesis ◽

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A globally convergent mean-field inference method in dense Markov random fields

2016 31st Youth Academic Annual Conference of Chinese Association of Automation (YAC) ◽

10.1109/yac.2016.7804902 ◽

2016 ◽

Author(s):

Hao Sun ◽

Xianqiang Yang

Keyword(s):

Random Fields ◽

Markov Random Fields ◽

Inference Method ◽

Globally Convergent ◽

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Mean field annealing using compound Gauss-Markov random fields for edge detection and image estimation

IEEE Transactions on Neural Networks ◽

10.1109/72.238324 ◽

1993 ◽

Vol 4 (4) ◽

pp. 703-709 ◽

Author(s):

J. Zerubia ◽

R. Chellappa

Keyword(s):

Edge Detection ◽

Random Fields ◽

Markov Random Fields ◽

Image Estimation ◽

Markov Random ◽

Field Annealing ◽

Gauss Markov Random Fields

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Processing CsI(Tl) 2-D matrices by means of neural networks and Markov random fields

IEEE Transactions on Nuclear Science ◽

10.1109/tns.2002.801704 ◽

2002 ◽

Vol 49 (4) ◽

pp. 1661-1668 ◽

Author(s):

M. Alderighi ◽

A. Anzalone ◽

R. Baruzzi ◽

G. Cardella ◽

E. De Filippo ◽

...

Keyword(s):

Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

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Variational phasor mean field model for Markov random fields

10.1109/isspa.2007.4555531 ◽

2007 ◽

Author(s):

Haruhisa Takahashi

Keyword(s):

Random Fields ◽

Markov Random Fields ◽

Field Model ◽

Mean Field Model ◽

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