Improving Semantic Image Segmentation With a Probabilistic Superpixel-Based Dense Conditional Random Field
Deep convolutional neural networks (DCNNs) have been driving significant advances in semantic image segmentation due to their powerful feature representation for recognition. However, their performance in preserving object boundaries is still not satisfactory. Visual mechanism theory indicates that...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2018-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8314143/ |