Concurrent Spatial and Channel ‘Squeeze & Excitation’ in Fully Convolutional Networks
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- 26 September 2018
- book chapter
- conference paper
- Published by Springer Science and Business Media LLC
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This publication has 8 references indexed in Scilit:
- Squeeze-and-Excitation NetworksPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2018
- Error Corrective Boosting for Learning Fully Convolutional Networks with Limited DataLecture Notes in Computer Science, 2017
- The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic SegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Deep Residual Learning for Image RecognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2016
- Learning Deconvolution Network for Semantic SegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- U-Net: Convolutional Networks for Biomedical Image SegmentationPublished by Springer Science and Business Media LLC ,2015
- Fully convolutional networks for semantic segmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Open Access Series of Imaging Studies: Longitudinal MRI Data in Nondemented and Demented Older AdultsJournal of Cognitive Neuroscience, 2010