Deep convolutional neural networks for semi-supervised learning from synthetic aperture sonar (SAS) images

Mapping Intimacies ◽

10.1121/2.0001018 ◽

2017 ◽

Author(s):

Johnny Chen ◽

Jason E. Summers

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Synthetic Aperture ◽

Deep Convolutional Neural Networks ◽

Synthetic Aperture Sonar

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Deep convolutional neural networks for semi-supervised learning from synthetic aperture sonar (SAS) images

The Journal of the Acoustical Society of America ◽

10.1121/1.4989020 ◽

2017 ◽

Vol 141 (5) ◽

pp. 3963-3963 ◽

Author(s):

Johnny L. Chen ◽

Jason E. Summers

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Synthetic Aperture ◽

Deep Convolutional Neural Networks ◽

Synthetic Aperture Sonar

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Underwater target classification in synthetic aperture sonar imagery using deep convolutional neural networks

2016 23rd International Conference on Pattern Recognition (ICPR) ◽

10.1109/icpr.2016.7900011 ◽

2016 ◽

Author(s):

David P. Williams

Keyword(s):

Neural Networks ◽

Convolutional Neural Networks ◽

Synthetic Aperture ◽

Target Classification ◽

Deep Convolutional Neural Networks ◽

Synthetic Aperture Sonar ◽

Underwater Target

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Weakly Supervised Learning with Deep Convolutional Neural Networks for Semantic Segmentation: Understanding Semantic Layout of Images with Minimum Human Supervision

IEEE Signal Processing Magazine ◽

10.1109/msp.2017.2742558 ◽

2017 ◽

Vol 34 (6) ◽

pp. 39-49 ◽

Author(s):

Seunghoon Hong ◽

Suha Kwak ◽

Bohyung Han

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Semantic Segmentation ◽

Deep Convolutional Neural Networks ◽

Weakly Supervised Learning ◽

Weakly Supervised

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Water body segmentation of Synthetic Aperture Radar image using Deep Convolutional Neural Networks

Microprocessors and Microsystems ◽

10.1016/j.micpro.2021.104360 ◽

2021 ◽

pp. 104360

Author(s):

R.Lalchhanhima ◽

Goutam Saha ◽

Samarendra Nath Sur ◽

Debdatta Kandar

Keyword(s):

Neural Networks ◽

Synthetic Aperture Radar ◽

Convolutional Neural Networks ◽

Synthetic Aperture Radar Image ◽

Radar Image ◽

Synthetic Aperture ◽

Deep Convolutional Neural Networks ◽

Body Segmentation ◽

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Playing Game 2048 with Deep Convolutional Neural Networks Trained by Supervised Learning

Journal of Information Processing ◽

10.2197/ipsjjip.27.340 ◽

2019 ◽

Vol 27 (0) ◽

pp. 340-347 ◽

Author(s):

Naoki Kondo ◽

Kiminori Matsuzaki

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Deep Convolutional Neural Networks

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WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks

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

10.1109/cvpr.2016.513 ◽

2016 ◽

Author(s):

Thibaut Durand ◽

Nicolas Thome ◽

Matthieu Cord

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Deep Convolutional Neural Networks ◽

Weakly Supervised Learning ◽

Weakly Supervised

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WALLACE: Weakly Supervised Learning of Deep Convolutional Neural Networks With Multiscale Evidence

IEEE Access ◽

10.1109/access.2020.2968545 ◽

2020 ◽

Vol 8 ◽

pp. 20449-20458

Author(s):

Yongsheng Liu ◽

Wenyu Chen ◽

Hong Qu ◽

Tianlei Wang ◽

Jiangzhou Ji ◽

...

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Deep Convolutional Neural Networks ◽

Weakly Supervised Learning ◽

Weakly Supervised

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Weakly-Supervised Learning of a Deep Convolutional Neural Networks for Semantic Segmentation

IEEE Access ◽

10.1109/access.2019.2926972 ◽

2019 ◽

Vol 7 ◽

pp. 91009-91018 ◽

Author(s):

Yanqing Feng ◽

Lunwen Wang ◽

Mengbo Zhang

Keyword(s):

Neural Networks ◽

Supervised Learning ◽

Convolutional Neural Networks ◽

Semantic Segmentation ◽

Deep Convolutional Neural Networks ◽

Weakly Supervised Learning ◽

Weakly Supervised

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RADARSAT-2 Synthetic-Aperture Radar Land Cover Segmentation Using Deep Convolutional Neural Networks

Pattern Recognition. ICPR International Workshops and Challenges - Lecture Notes in Computer Science ◽

10.1007/978-3-030-68793-9_8 ◽

2021 ◽

pp. 106-117

Author(s):

Mirmohammad Saadati ◽

Marco Pedersoli ◽

Patrick Cardinal ◽

Peter Oliver

Keyword(s):

Neural Networks ◽

Synthetic Aperture Radar ◽

Convolutional Neural Networks ◽

Synthetic Aperture ◽

Deep Convolutional Neural Networks ◽

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Subsidence feature discrimination using deep convolutional neural networks in synthetic aperture radar imagery

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

10.1109/igarss.2017.8128031 ◽

2017 ◽

Author(s):

C. P. Schwegmann ◽

W. Kleynhans ◽

J. Engelbrecht ◽

L. W. Mdakane ◽

R. G. V. Meyer

Keyword(s):

Neural Networks ◽

Synthetic Aperture Radar ◽

Convolutional Neural Networks ◽

Synthetic Aperture ◽

Deep Convolutional Neural Networks ◽

Radar Imagery ◽

Synthetic Aperture Radar Imagery ◽

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