Parallel global convolutional network for semantic image segmentation
Abstract In this paper, a novel convolutional neural network for fast semantic segmentation is presented. Deep convolutional neural networks have achieved great progress in the task of vision scene understanding. While the increase of the accuracy mainly depends on the increase of depth and width. T...
Main Authors: | Xing Bai, Jun Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
|
Series: | IET Image Processing |
Online Access: | https://doi.org/10.1049/ipr2.12025 |
Similar Items
-
Parallel Fully Convolutional Network for Semantic Segmentation
by: Jian Ji, et al.
Published: (2021-01-01) -
Dense Convolutional Networks for Semantic Segmentation
by: Chaoyi Han, et al.
Published: (2019-01-01) -
[en] CONVOLUTIONAL NETWORKS APPLIED TO SEMANTIC SEGMENTATION OF SEISMIC IMAGES
Published: (2021) -
Semantic Segmentation via Global Convolutional Network and Concatenated Feature Maps
by: Wang, Chuan-Kai, et al.
Published: (2018) -
Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation
by: Dang N.H. Thanh, et al.
Published: (2021-02-01)