Conditional Random Fields as Recurrent Neural Networks

2015 IEEE International Conference on Computer Vision (ICCV) ◽

10.1109/iccv.2015.179 ◽

2015 ◽

Cited By ~ 904

Author(s):

Shuai Zheng ◽

Sadeep Jayasumana ◽

Bernardino Romera-Paredes ◽

Vibhav Vineet ◽

Zhizhong Su ◽

...

Keyword(s):

Neural Networks ◽

Recurrent Neural Networks ◽

Random Fields ◽

Conditional Random Fields

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Context-based conditional random fields as recurrent neural networks for image labeling

Multimedia Tools and Applications ◽

10.1007/s11042-019-7564-x ◽

2019 ◽

Vol 79 (23-24) ◽

pp. 17135-17145 ◽

Cited By ~ 1

Author(s):

Kun Hu ◽

Shuyou Zhang ◽

Xinyue Zhao

Keyword(s):

Neural Networks ◽

Recurrent Neural Networks ◽

Random Fields ◽

Conditional Random Fields ◽

Image Labeling

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Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks

Database ◽

10.1093/database/baw140 ◽

2016 ◽

Vol 2016 ◽

pp. baw140 ◽

Cited By ~ 28

Author(s):

Qikang Wei ◽

Tao Chen ◽

Ruifeng Xu ◽

Yulan He ◽

Lin Gui

Keyword(s):

Neural Networks ◽

Recurrent Neural Networks ◽

Random Fields ◽

Conditional Random Fields ◽

Named Entity Recognition ◽

Entity Recognition ◽

Named Entity

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Object-based affordances detection with Convolutional Neural Networks and dense Conditional Random Fields

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) ◽

10.1109/iros.2017.8206484 ◽

2017 ◽

Cited By ~ 32

Author(s):

Anh Nguyen ◽

Dimitrios Kanoulas ◽

Darwin G. Caldwell ◽

Nikos G. Tsagarakis

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Conditional Random Fields ◽

Object Based

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Combination of Neural Networks and Conditional Random Fields for Efficient Resume Parsing

2018 International CET Conference on Control, Communication, and Computing (IC4) ◽

10.1109/cetic4.2018.8530883 ◽

2018 ◽

Cited By ~ 1

Author(s):

C H Ayishathahira ◽

C Sreejith ◽

C Raseek

Keyword(s):

Neural Networks ◽

Random Fields ◽

Conditional Random Fields

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Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction

IEEE Signal Processing Magazine ◽

10.1109/msp.2017.2762355 ◽

2018 ◽

Vol 35 (1) ◽

pp. 37-52 ◽

Cited By ~ 36

Author(s):

Anurag Arnab ◽

Shuai Zheng ◽

Sadeep Jayasumana ◽

Bernardino Romera-Paredes ◽

Mans Larsson ◽

...

Keyword(s):

Neural Networks ◽

Deep Learning ◽

Graphical Models ◽

Random Fields ◽

Deep Neural Networks ◽

Conditional Random Fields ◽

Probabilistic Graphical Models ◽

Semantic Segmentation ◽

Structured Prediction

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Combining heterogeneous deep neural networks with conditional random fields for Chinese dialogue act recognition

Neurocomputing ◽

10.1016/j.neucom.2015.05.086 ◽

2015 ◽

Vol 168 ◽

pp. 408-417 ◽

Cited By ~ 16

Author(s):

Yucan Zhou ◽

Qinghua Hu ◽

Jie Liu ◽

Yuan Jia

Keyword(s):

Neural Networks ◽

Random Fields ◽

Deep Neural Networks ◽

Conditional Random Fields

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Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016 - Lecture Notes in Computer Science ◽

10.1007/978-3-319-46723-8_48 ◽

2016 ◽

pp. 415-423 ◽

Cited By ~ 139

Author(s):

Patrick Ferdinand Christ ◽

Mohamed Ezzeldin A. Elshaer ◽

Florian Ettlinger ◽

Sunil Tatavarty ◽

Marc Bickel ◽

...

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Conditional Random Fields ◽

Lesion Segmentation ◽

Fully Convolutional Neural Networks

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Environmental microorganism classification using conditional random fields and deep convolutional neural networks

Pattern Recognition ◽

10.1016/j.patcog.2017.12.021 ◽

2018 ◽

Vol 77 ◽

pp. 248-261 ◽

Cited By ~ 21

Author(s):

Sergey Kosov ◽

Kimiaki Shirahama ◽

Chen Li ◽

Marcin Grzegorzek

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Conditional Random Fields ◽

Deep Convolutional Neural Networks ◽

Microorganism Classification ◽

Environmental Microorganism

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Development of Artificial Neural Networks with Integrated Conditional Random Fields Capable of Predicting Non-linear Dynamics of the Flow Around Cylinders

Notes on Numerical Fluid Mechanics and Multidisciplinary Design - New Results in Numerical and Experimental Fluid Mechanics XII ◽

10.1007/978-3-030-25253-3_7 ◽

2019 ◽

pp. 71-79

Author(s):

Sebastian Herzog ◽

Claus Wagner

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Random Fields ◽

Conditional Random Fields ◽

Linear Dynamics ◽

Non Linear ◽

Artificial Neural

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Left Atrial Appendage Segmentation Using Fully Convolutional Neural Networks and Modified Three-Dimensional Conditional Random Fields

IEEE Journal of Biomedical and Health Informatics ◽

10.1109/jbhi.2018.2794552 ◽

2018 ◽

Vol 22 (6) ◽

pp. 1906-1916 ◽

Cited By ~ 8

Author(s):

Cheng Jin ◽

Jianjiang Feng ◽

Lei Wang ◽

Heng Yu ◽

Jiang Liu ◽

...

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Random Fields ◽

Left Atrial ◽

Conditional Random Fields ◽

Left Atrial Appendage ◽

Three Dimensional ◽

Atrial Appendage ◽

Fully Convolutional Neural Networks

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