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Open AccessArticle

Automatic Raft Labeling for Remote Sensing Images via Dual-Scale Homogeneous Convolutional Neural Network

by Tianyang Shi 1,2, Qizhi Xu 3,*, Zhengxia Zou 1,2,* and Zhenwei Shi 1,2,*
1
Image Processing Center, School of Astronautics, Beihang University, Beijing 100191, China
2
State Key Laboratory of Virtual Reality Technology and Systems, School of Astronautics, Beihang University, Beijing 100191, China
3
Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, China
*
Authors to whom correspondence should be addressed.
Remote Sens. 2018, 10(7), 1130; https://doi.org/10.3390/rs10071130
Received: 5 June 2018 / Revised: 30 June 2018 / Accepted: 14 July 2018 / Published: 18 July 2018
(This article belongs to the Special Issue Recent Advances in Neural Networks for Remote Sensing)
Raft-culture is a way of utilizing water for farming aquatic product. Automatic raft-culture monitoring by remote sensing technique is an important way to control the crop’s growth and implement effective management. This paper presents an automatic pixel-wise raft labeling method based on fully convolutional network (FCN). As rafts are always tiny and neatly arranged in images, traditional FCN method fails to extract the clear boundary and other detailed information. Therefore, a homogeneous convolutional neural network (HCN) is designed, which only consists of convolutions and activations to retain all details. We further design a dual-scale structure (DS-HCN) to integrate higher-level contextual information for accomplishing sea–land segmentation and raft labeling at the same time in a uniform framework. A dataset with Gaofen-1 satellite images was collected to verify the effectiveness of our method. DS-HCN shows a satisfactory performance with a better interpretability and a more accurate labeling result. View Full-Text
Keywords: raft-culture; remote sensing; raft labeling; dual-scale; convolutional neural network raft-culture; remote sensing; raft labeling; dual-scale; convolutional neural network
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MDPI and ACS Style

Shi, T.; Xu, Q.; Zou, Z.; Shi, Z. Automatic Raft Labeling for Remote Sensing Images via Dual-Scale Homogeneous Convolutional Neural Network. Remote Sens. 2018, 10, 1130.

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