TY - GEN
T1 - Accurate ship segmentation via ship contour prediction
AU - Xiao, Xiaowu
AU - Ai, Changjun
AU - Wang, Weishen
AU - Zhou, Zhiqiang
AU - Li, Linhao
AU - Chu, Jun
N1 - Publisher Copyright:
© 2020 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2020/7
Y1 - 2020/7
N2 - Accurate ship segmentation in optical remote sensing images is challenging. In this paper, ship contour prediction network is introduced to improve the performance of ship segmentation network. Ship contour prediction network predicts the ship contour, which can promote the learning of ship segmentation network, producing more accurate segmentation results. The ship contour prediction network can be naturally embedded into any ship segmentation network with encoder-decoder architecture. Moreover, ship contour prediction network is only used in the training process, and thus the network not only can improve segmentation accuracy, but also does not increase computational cost in the testing process.
AB - Accurate ship segmentation in optical remote sensing images is challenging. In this paper, ship contour prediction network is introduced to improve the performance of ship segmentation network. Ship contour prediction network predicts the ship contour, which can promote the learning of ship segmentation network, producing more accurate segmentation results. The ship contour prediction network can be naturally embedded into any ship segmentation network with encoder-decoder architecture. Moreover, ship contour prediction network is only used in the training process, and thus the network not only can improve segmentation accuracy, but also does not increase computational cost in the testing process.
KW - Convolutional neural network
KW - Fully convolutional network
KW - Semantic segmentation
KW - Ship contour prediction
KW - Ship segmentation
UR - http://www.scopus.com/inward/record.url?scp=85091400261&partnerID=8YFLogxK
U2 - 10.23919/CCC50068.2020.9188658
DO - 10.23919/CCC50068.2020.9188658
M3 - Conference contribution
AN - SCOPUS:85091400261
T3 - Chinese Control Conference, CCC
SP - 7402
EP - 7405
BT - Proceedings of the 39th Chinese Control Conference, CCC 2020
A2 - Fu, Jun
A2 - Sun, Jian
PB - IEEE Computer Society
T2 - 39th Chinese Control Conference, CCC 2020
Y2 - 27 July 2020 through 29 July 2020
ER -