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

2001 IEEE Nuclear Science Symposium Conference Record (Cat. No.01CH37310) ◽

10.1109/nssmic.2001.1008465 ◽

2005 ◽

Author(s):

M. Alderighi ◽

A. Anzalone ◽

R. Baruzzi ◽

G. Cardella ◽

S. Cavallaro ◽

...

Keyword(s):

Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Download Full-text

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

Download Full-text

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 ◽

Download Full-text

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 ◽

Download Full-text

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 ◽

Download Full-text

Stochastic approach to texture analysis using probabilistic neural networks and Markov random fields

10.1117/12.292761 ◽

1997 ◽

Author(s):

Jamshid Dehmeshki ◽

Mohammad F. Daemi ◽

Fraser N. Hatfield ◽

Mehdi Rashidi

Keyword(s):

Neural Networks ◽

Texture Analysis ◽

Random Fields ◽

Markov Random Fields ◽

Stochastic Approach ◽

Probabilistic Neural Networks ◽

Download Full-text

Segmentation of seafloor sidescan imagery using Markov random fields and neural networks

Proceedings of OCEANS '93 ◽

10.1109/oceans.1993.326232 ◽

2002 ◽

Author(s):

M. Jiang ◽

W.K. Stewart ◽

M. Marra

Keyword(s):

Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Download Full-text

Layout design using neural networks and Markov random fields

Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan) ◽

10.1109/ijcnn.1993.714030 ◽

2005 ◽

Author(s):

G. Paass

Keyword(s):

Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Layout Design ◽

Download Full-text

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 ◽

Download Full-text

Markov Random Fields and Neural Networks with Applications to Early Vision Problems

Artificial Neural Networks and Statistical Pattern Recognition - Old and New Connections - Machine Intelligence and Pattern Recognition ◽

10.1016/b978-0-444-88740-5.50014-1 ◽

1991 ◽

pp. 155-174 ◽

Author(s):

A. Rangarajan ◽

R. Chellappa ◽

B.S. Manjunath

Keyword(s):

Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Early Vision ◽

Download Full-text

Data-Independent Feature Learning with Markov Random Fields in Convolutional Neural Networks

Neurocomputing ◽

10.1016/j.neucom.2019.03.107 ◽

2020 ◽

Vol 378 ◽

pp. 24-35

Author(s):

Yao Peng ◽

Richard Hankins ◽

Hujun Yin

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Markov Random Fields ◽

Feature Learning ◽

Download Full-text