Deep Multi-scale Convolutional Neural Network for Hyperspectral Image Classification

机译：深度多尺度卷积神经网络用于高光谱图像分类

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

机译：在本文中，我们提出了一种用于高光谱图像分类任务的多尺度卷积神经网络。首先，与常规卷积相比，我们利用具有较大各自场的多尺度卷积来提取高光谱图像的光谱特征。我们设计了一个具有多尺度卷积层的深度神经网络，其中包含3种不同的卷积核大小。其次，为避免深度神经网络的过度拟合，利用了辍学机制，该机制使神经元随机进入睡眠状态，从而有助于稍微提高分类的准确性。此外，本文还利用了诸如深度学习中的ReLU之类的新技能。我们对帕维亚大学和萨利纳斯大学的数据集进行了实验，与其他方法相比，获得了更好的分类准确性。

著录项

来源
《International conference on graphic and image processing》|2017年|106152Z.1-106152Z.7|共7页
会议地点
作者
ZHANG Feng-zhe; YANG Xia;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类
关键词
hyperspectral image; multi-scale convolution; image classification; deep learning;

机译：高光谱图像多尺度卷积图像分类;深度学习;

相似文献

外文文献
中文文献
专利

1. Deep Feature Extraction and Classification of Hyperspectral Images Based on Convolutional Neural Networks [J] . Yushi Chen, Hanlu Jiang, Chunyang Li, IEEE Transactions on Geoscience and Remote Sensing . 2016,第10期

机译：基于卷积神经网络的高光谱图像深度特征提取与分类
2. Spectral-spatial classification of hyperspectral images using deep convolutional neural networks [J] . Yue Jun, Zhao Wenzhi, Mao Shanjun, Remote sensing letters . 2015,第4a6期

机译：利用深度卷积神经网络对高光谱图像进行光谱空间分类
3. Multi-Scale Dilated Convolutional Neural Network for Hyperspectral Image Classification [J] . Shanshan Zheng, Wen Liu, Rui Shan, 哈尔滨工业大学学报（英文版） . 2021,第004期

机译：用于高光谱图像分类的多尺度扩张卷积神经网络
4. Multi-scale 3D deep convolutional neural network for hyperspectral image classification [C] . Mingyi He, Bo Li, Huahui Chen IEEE International Conference on Image Processing . 2017

机译：用于高光谱图像分类的多尺度3D深卷积神经网络
5. Deep convolutional neural networks for classification of fused hyperspectral and LiDAR data. [D] . Morchhale, Saurabh. 2016

机译：深度卷积神经网络，用于融合高光谱和LiDAR数据。
6. Hierarchical Multi-Scale Convolutional Neural Networks for Hyperspectral Image Classification [O] . Simin Li, Xueyu Zhu, Jie Bao 2019

机译：高光谱图像分类的分层多尺度卷积神经网络
7. Modified Convolutional Neural Networks Architecture for Hyperspectral Image Classification (Extra‐Convolutional Neural Networks) [O] . Maissa HAMOUDA, Med Salim BOUHLEL 2021

机译：用于高光谱图像分类的修改的卷积神经网络（超卷积神经网络）

Deep Multi-scale Convolutional Neural Network for Hyperspectral Image Classification

摘要

著录项

相似文献

相关主题

期刊订阅