基于effentnet的遥感图像分类算法研究

2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP) Pub Date : 2022-04-15 DOI:10.1109/ICSP54964.2022.9778437

Hang Yin, Cheng Yang, Jiayi Lu

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引用次数: 1

摘要

遥感影像的准确分类在遥感应用中具有重要意义。为了验证efficientnet算法在遥感影像分类中的效率和准确性，本文基于efficientnet对UCMerced LandUse数据集进行了分类。实验结果表明，与VGGNet、ResNet和MobileNet相比，effentnet网络引入了复合参数，同时对深度、宽度和分辨率进行了缩放。验证集中的EfficientV2-s的准确率比VGG、MobileNetV2、ResNet34和EfficientNet-b0分别高出16.5%、5.2%、1.8%和1.7%，显示了EfficientNet网络在遥感图像分类数据集中的效率和准确性。

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Research on Remote Sensing Image Classification Algorithm Based on EfficientNet

Accurate classification of remote sensing images is important in remote sensing applications. In order to verify the efficiency and accuracy of efficientnet algorithm in remote sensing image classification, this paper classifies the UCMerced LandUse dataset based on EfficientNet. The experimental results show that compared with VGGNet, ResNet and MobileNet, the EfficientNet network introduces composite parameters and scales depth, width and resolution at the same time. The accuracy of EfficientV2-s in the verification set is 16.5%, 5.2%, 1.8% and 1.7% higher than that of VGG, MobileNetV2, ResNet34 and EfficientNet-b0, which shows the efficiency and accuracy of EfficientNet network in remote sensing image classification data set.

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2022 7th International Conference on Intelligent Computing and Signal Processing (ICSP)

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