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An Encoder-Decoder Network Based FCN Architecture for Semantic Segmentation
Joint Authors
Zhong, Luo
Xing, Yongfeng
Zhong, Xian
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-07
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
In recent years, the convolutional neural network (CNN) has made remarkable achievements in semantic segmentation.
The method of semantic segmentation has a desirable application prospect.
Nowadays, the methods mostly use an encoder-decoder architecture as a way of generating pixel by pixel segmentation prediction.
The encoder is for extracting feature maps and decoder for recovering feature map resolution.
An improved semantic segmentation method on the basis of the encoder-decoder architecture is proposed.
We can get better segmentation accuracy on several hard classes and reduce the computational complexity significantly.
This is possible by modifying the backbone and some refining techniques.
Finally, after some processing, the framework has achieved good performance in many datasets.
In comparison with the traditional architecture, our architecture does not need additional decoding layer and further reuses the encoder weight, thus reducing the complete quantity of parameters needed for processing.
In this paper, a modified focal loss function is also put forward, as a replacement for the cross-entropy function to achieve a better treatment of the imbalance problem of the training data.
In addition, more context information is added to the decode module as a way of improving the segmentation results.
Experiments prove that the presented method can get better segmentation results.
As an integral part of a smart city, multimedia information plays an important role.
Semantic segmentation is an important basic technology for building a smart city.
American Psychological Association (APA)
Xing, Yongfeng& Zhong, Luo& Zhong, Xian. 2020. An Encoder-Decoder Network Based FCN Architecture for Semantic Segmentation. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1214779
Modern Language Association (MLA)
Xing, Yongfeng…[et al.]. An Encoder-Decoder Network Based FCN Architecture for Semantic Segmentation. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1214779
American Medical Association (AMA)
Xing, Yongfeng& Zhong, Luo& Zhong, Xian. An Encoder-Decoder Network Based FCN Architecture for Semantic Segmentation. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1214779
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214779