Semantic Segmentation for Identifying Road Surface Damages Using Lightweight Encoder-Decoder Network
Author:
Affiliation:
1. Telkom University,School of Computing,Bandung,Indonesia
2. Carnegie Mellon University,Department of Mechanical Engineering,Pittsburgh,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10054513/10054684/10056030.pdf?arnumber=10056030
Reference19 articles.
1. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
2. Fully convolutional networks for semantic segmentation
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4. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
5. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc of the Int Conf on Medical Image Computing and Computer-assisted Intervention,2015
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