Hardware-Aware Design of Speed-Up Algorithms for Synthetic Aperture Radar Ship Target Detection Networks

Recently, synthetic aperture radar (SAR) target detection algorithms based on Convolutional Neural Networks (CNN) have received increasing attention. However, the large amount of computation required burdens the real-time detection of SAR ship targets on resource-limited and power-constrained satell...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 15; no. 20; p. 4995
Main Authors:	Zhang, Yue, Jiang, Shuai, Cao, Yue, Xiao, Jiarong, Li, Chengkun, Zhou, Xuan, Yu, Zhongjun
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.10.2023
Subjects:	Acceleration Accuracy Algorithms Artificial intelligence Artificial neural networks Comparative analysis Compressing convolutional neural networks (CNN) data collection graphic processing unit (GPU) Graphics processing units Hardware Identification and classification Information processing model speed-up algorithms Neural networks Parameter estimation Radar Radar detection Remote sensing satellites Ships Statistical methods Synthetic aperture radar synthetic aperture radar (SAR) Target detection China
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
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