Feature Enhanced Fully Convolutional Network for Ship Detection
Author:
Publisher
China Science Publishing & Media Ltd.
Subject
Computer Graphics and Computer-Aided Design,Software
Link
https://engine.scichina.com/doi/pdf/A85DE19C22F2407B837958F4936072F4
Reference29 articles.
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2. Ribeiro R, Cruz G, Matos J. A data set for airborne maritime surveillance environments. IEEE Transactions on Circuits and Systems for Video Technology, 2019, 29: 2720-2732.
3. Shao Z F, Wu W J, Wang Z Y. SeaShips: a large-scale precisely annotated dataset for ship detection. IEEE Transactions on Multimedia, 2018, 20: 2593-2604.
4. Shao Z F, Wang L G, Wang Z Y. Saliency-aware convolution neural network for ship detection in surveillance video. IEEE Transactions on Circuits and Systems for Video Technology, 2020, 30: 781-794.
5. Zhang Y, Li Q Z, Zang F N. Ship detection for visual maritime surveillance from non-stationary platforms. Ocean Engineering, 2017, 141: 53-63.
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