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MLS-net: An efficient convolutional network for multi-scale..:

, In: International Conference on Radar Systems (RADAR 2022),

Zhang, Y. ; Wang, X. ; Jiang, Z... - p. None , 2022

Link: https://doi.org/10.1049/ICP.2023.1274

RT 
T1 <cTitle>International Conference on Radar Systems (RADAR 2022)</cTitle>: T1 <Title>MLS-net: An efficient convolutional network for multi-scale ship detection in SAR images</Title>

UL https://suche.suub.uni-bremen.de/peid=ieee-10106379&Exemplar=1&LAN=DE
				
A1 Zhang, Y.
A1 Wang, X.
A1 Jiang, Z.
A1 Li, G.
A1 He, Y.
YR 2022
K1 convolutional neural nets
K1 feature extraction
K1 image classification
K1 object detection
K1 radar computing
K1 radar imaging
K1 ships
K1 synthetic aperture radar
K1 efficient convolutional network
K1 efficient convolutional neural network-based detector
K1 extremely lightweight backbone network
K1 feature fusion sub-network
K1 feature maps
K1 high-level semantic features
K1 MLS-based detection heads
K1 MLS-net
K1 MLS-Net
K1 multilevel supervision strategy
K1 multiscale feature aggregation modules
K1 multiscale ship detection
K1 multiscale ship targets
K1 open SAR ship dataset SSDD show
K1 SAR image features
K1 SAR images
K1 similar detection performance
K1 synthetic aperture radar images
SP None
LK http://dx.doi.org/https://doi.org/10.1049/ICP.2023.1274
DO https://doi.org/10.1049/ICP.2023.1274
SF ELIB - SuUB Bremen

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