| 卷积神经网络识别侧扫声呐影像的研究 |
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| 引用本文： | 张博宇,王晓,杨敬华,朱邦彦.卷积神经网络识别侧扫声呐影像的研究[J].海洋科学进展,2022,40(1):102-109. |
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| 作者姓名： | 张博宇 王晓 杨敬华 朱邦彦 |
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| 作者单位： | 江苏海洋大学海洋技术与测绘学院;南京市测绘勘察研究院股份有限公司 |
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| 基金项目： | 国家自然科学基金项目——复杂背景特征下侧扫声呐图像目标自动探测方法研究(41806117)。 |
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| 摘 要： | 卷积神经网络是当前应用最广泛的图像识别算法,利用大量数据对网络进行训练,即可达到快速、高效地对图像进行识别的目的 .由于卷积神经网络结构众多,且同一数据在不同网络表现也不尽相同,为了选择适用于分析沉船声呐数据的网络,使用Python搭建LeNet 5、AlexNet、VGG、GoogLeNet、ResNet系列(Res...
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| 关 键 词： | 卷积神经网络 侧扫声呐图像 沉船识别 |
Research on Convolutional Neural Network Model for Image Recognition in Side Scan Sonar |
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| ZHANG Bo-yu,WANG Xiao,YANG Jing-hua,ZHU Bang-yan.Research on Convolutional Neural Network Model for Image Recognition in Side Scan Sonar[J].Advances in Marine Science,2022,40(1):102-109. |
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| Authors: | ZHANG Bo-yu WANG Xiao YANG Jing-hua ZHU Bang-yan |
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| Institution: | (School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222000, China;Nanjing Institute of Surveying, Mapping & Geotechnical Investigation, Co. Ltd., Nanjing 210019, China) |
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| Abstract: | Convolutional neural network is currently the most widely used image recognition algorithm.It can achieve the purpose of image recognition quickly and efficiently by training the network with a large amount of data.However,the convolutional neural network has numerous structures,and the same data has different performance in different network.In order to explore the suitable popular network for sunken sonar data,eleven convolutional neural network structure,which are LeNet-5,AlexNet,VGG,GoogleNet,ResNet50,ResNet101,ResNet152,DenSeNet121,DenSeNet169,DenSeNet201 and DenSeNet264,are constructed by Python.Further,the shipwreck images of side-scan sonar are used as the data set for the experiment.The results show that DenSeNet121 is the most suitable network structure for underwater sunken ship image recognition among the those networks. |
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| Keywords: | convolutional neural network side scan sonar image shipwreck recognition |
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