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

Random Fields ◽

Lesion Segmentation ◽

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 ◽

Random Fields ◽

Left Atrial ◽

Left Atrial Appendage ◽

Three Dimensional ◽

Atrial Appendage ◽

Skin lesion segmentation using object scale-oriented fully convolutional neural networks

Signal Image and Video Processing ◽

10.1007/s11760-018-01410-3 ◽

2019 ◽

Vol 13 (3) ◽

pp. 431-438 ◽

Cited By ~ 9

Author(s):

Lin Huang ◽

Yi-gong Zhao ◽

Tie-jun Yang

Keyword(s):

Neural Networks ◽

Skin Lesion ◽

Lesion Segmentation ◽

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 ◽

Random Fields ◽

Object Based

Advances in Intelligent Systems and Computing - Advanced Intelligent Systems for Sustainable Development (AI2SD’2019) ◽

Ischemic Stroke Lesion Segmentation Based on Thermal Analysis Model Using U-Net Fully Convolutional Neural Networks on GPUs

10.1007/978-3-030-36677-3_12 ◽

2020 ◽

pp. 99-106

Author(s):

Abdelmajid Bousselham ◽

Omar Bouattane ◽

Mohamed Youssfi ◽

Abdelhadi Raihani

Keyword(s):

Neural Networks ◽

Thermal Analysis ◽

Ischemic Stroke ◽

Lesion Segmentation ◽

Analysis Model ◽

Fully Convolutional Neural Networks ◽

Stroke Lesion

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 ◽

Random Fields ◽

Deep Convolutional Neural Networks ◽

Microorganism Classification ◽

Environmental Microorganism

Road Segmentation of Remotely-Sensed Images Using Deep Convolutional Neural Networks with Landscape Metrics and Conditional Random Fields

Remote Sensing ◽

10.3390/rs9070680 ◽

2017 ◽

Vol 9 (7) ◽

pp. 680 ◽

Cited By ~ 38

Author(s):

Teerapong Panboonyuen ◽

Kulsawasd Jitkajornwanich ◽

Siam Lawawirojwong ◽

Panu Srestasathiern ◽

Peerapon Vateekul

Keyword(s):

Neural Networks ◽

Landscape Metrics ◽

Random Fields ◽

Remotely Sensed ◽

Deep Convolutional Neural Networks ◽

Remotely Sensed Images ◽

Road Segmentation

Conditional random fields incorporate convolutional neural networks for human eye sclera semantic segmentation

2017 IEEE International Joint Conference on Biometrics (IJCB) ◽

10.1109/btas.2017.8272768 ◽

2017 ◽

Cited By ~ 2

Author(s):

Russel Mesbah ◽

Brendan McCane ◽

Steven Mills

Keyword(s):

Neural Networks ◽

Random Fields ◽

Semantic Segmentation ◽

Human Eye

Automatic meniscus segmentation using cascaded deep convolutional neural networks with 2D conditional random fields in knee MR images

International Workshop on Advanced Imaging Technology (IWAIT) 2020 ◽

10.1117/12.2566450 ◽

2020 ◽

Author(s):

UJU JEON ◽

HYEONJIN KIM ◽

HELEN HONG ◽

JOONHO WANG

Keyword(s):

Neural Networks ◽

Random Fields ◽

Deep Convolutional Neural Networks

Mr Images ◽

2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017) ◽

Spatio-Temporal Facial Expression Recognition Using Convolutional Neural Networks and Conditional Random Fields

10.1109/fg.2017.99 ◽

2017 ◽

Cited By ~ 24

Author(s):

Behzad Hasani ◽

Mohammad H. Mahoor

Keyword(s):

Neural Networks ◽

Facial Expression ◽

Random Fields ◽

Facial Expression Recognition ◽

Expression Recognition ◽

Spatio Temporal

Fully Convolutional Neural Networks for Automotive Radar Interference Mitigation

2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall) ◽

10.1109/vtc2020-fall49728.2020.9348690 ◽

2020 ◽

Author(s):

Nicolae-Catalin Ristea ◽

Andrei Anghel ◽

Radu Tudor Ionescu

Keyword(s):

Neural Networks ◽

Interference Mitigation ◽

Automotive Radar ◽