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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Vydáno v:	Remote sensing (Basel, Switzerland) Ročník 15; číslo 20; s. 4995
Hlavní autoři:	Zhang, Yue, Jiang, Shuai, Cao, Yue, Xiao, Jiarong, Li, Chengkun, Zhou, Xuan, Yu, Zhongjun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.10.2023
Témata:	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
On-line přístup:	Získat plný text
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