Art

J-GLOBAL ID：201802218255727786   Reference number：18A1073268

Contextual Region-Based Convolutional Neural Network with Multilayer Fusion for SAR Ship Detection

SAR船舶検出のための多層融合による文脈領域ベース畳込みニューラルネットワーク【JST・京大機械翻訳】

Author (4)： Kang Miao (School of Electronic Science and Engineering, National University of Defense Technology, Sanyi Avenue, Changsha 410073, China) ,  Ji Kefeng (School of Electronic Science and Engineering, National University of Defense Technology, Sanyi Avenue, Changsha 410073, China) ,  Leng Xiangguang (School of Electronic Science and Engineering, National University of Defense Technology, Sanyi Avenue, Changsha 410073, China) ,  Lin Zhao (School of Electronic Science and Engineering, National University of Defense Technology, Sanyi Avenue, Changsha 410073, China)
Material： Remote Sensing (Web)
Volume： 9  Issue： 8  Page： 860  Publication year： 2017 
JST Material Number： U7270A  ISSN： 2072-4292  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Synthetic aperture radar (SAR)...

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Thesaurus term： synthetic-aperture radar ,  *neural network (biomodel) ,  computer vision ,  image ,  *ship ,  normalization ,  ocean ,  *multilayer ,  monolayer ,  *network ,  high-resolution ,  error alarm ,  feature vector ,  object detection
Semi thesaurus term： SAR画像 ,  低分解能 , 【Automatic Indexing@JST】

Author keywords (5)： context information ,  convolutional neural network (CNN) ,  ship detection ,  synthetic aperture radar (SAR) ,  Sentinel-1

JST classification (4)： Radar  (ND13010H) ,  Graphic and image processing in general  (JE04010I) ,  Pattern recognition  (JE07000S) ,  Remote sensing in general  (AD04000L)

Reference (37)：

• Brusch, S.; Lehner, S.; Fritz, T.; Soccorsi, M. Ship suveillance with TerraSAR-X. IEEE Trans. Geosci. Remote Sens. 2011, 49, 1092-1103.
• Crisp, D.J. A ship detection system for RADARSAT-2 dual-pol multi-look imagery implemented in the ADSS. In Proceedings of the 2013 IEEE International Conference on Radar, Adelaide, Australia, 9-12 September 2013; pp. 318-323.
• Torres, R.; Snoeij, P.; Geudtner, D.; Bibby, D.; Davidson, M.; Attema, E.; Potin, P.; Rommen, B.; Floury, N.; Brown, M.; et al. GMES Sentinel-1 mission. Remote Sens. Environ. 2012, 120, 9-24.
• Crisp, D.J. The state-of-the-art in ship detection in Synthetic Aperture Radar imagery. Org. Lett. 2004, 35, 2165-2168.
• Marino, A.; Sugimoto, M.; Ouchi, K.; Hajnsek, I. Validating a Notch Filter for Detection of Targets at Sea with ALOS-PALSAR Data: Tokyo Bay. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2014, 7, 74907-74918.

Terms in the title (6)： SAR ,  船舶 ,  多層 ,  融合 ,  文脈 ,  畳込みニューラルネットワーク