A Comparison: Different DCNN Models for Intelligent Object Detection in Remote Sensing Images

doi:10.1007/s11063-018-9878-5

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	A Comparison: Different DCNN Models for Intelligent Object Detection in Remote Sensing Images
	Ding, Peng; Zhang, Ye; Jia, Ping; Chang, Xu-ling
	2018
发表期刊	Neural Processing Letters
ISSN	13704621
卷号	0 页码:2019-01-11
摘要	In recent years, deep learning especially deep convolutional neural networks (DCNN) has made great progress. Many researchers take advantage of different DCNN models to do object detection in remote sensing. Different DCNN models have different advantages and disadvantages. But in the field of remote sensing, many scholars usually do comparison between DCNN models and traditional machine learning. In this paper, we compare different state-of-the-art DCNN models mainly over two publicly available remote sensing datasetsairplane dataset and car dataset. Such comparison can provide guidance for related researchers. Besides,we provide suggestions for fine-tuning different DCNN models. Moreover, for DCNN models including fully connected layers, we provide a method to save storage space. 2018 Springer Science+Business Media, LLC, part of Springer Nature
关键词	Remote sensing Computer vision Convolution Deep learning Deep neural networks Neural networks Object detection Object recognition Space optics
DOI	10.1007/s11063-018-9878-5
收录类别	EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/60557
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	Ding, Peng,Zhang, Ye,Jia, Ping,et al. A Comparison: Different DCNN Models for Intelligent Object Detection in Remote Sensing Images[J]. Neural Processing Letters,2018,0:2019-01-11.
APA	Ding, Peng,Zhang, Ye,Jia, Ping,&Chang, Xu-ling.(2018).A Comparison: Different DCNN Models for Intelligent Object Detection in Remote Sensing Images.Neural Processing Letters,0,2019-01-11.
MLA	Ding, Peng,et al."A Comparison: Different DCNN Models for Intelligent Object Detection in Remote Sensing Images".Neural Processing Letters 0(2018):2019-01-11.

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