[HTML][HTML] 深度学习在雷达中的研究综述
王俊， 郑彤， 雷鹏， 魏少明 - 雷达学报, 2018 - radars.ac.cn
王俊(1972–), 男, 教授. 现于北京航空航天大学电子信息工程学院从事科研教学工作. 1995
年于西北工业大学获通信工程专业工学学士学位, 1998 年, 2001 年于北京航空航天大学分别获 …
年于西北工业大学获通信工程专业工学学士学位, 1998 年, 2001 年于北京航空航天大学分别获 …
[HTML][HTML] Study on deep learning in radar
W Jun, Z Tong, L Peng, W Shaoming - 雷达学报, 2018 - radars.ac.cn
Electromagnetic waves are transmitted by radars and reflected by different objects, and
radar signal processing is highly significant as its analyses can lead to the acquisition of …
radar signal processing is highly significant as its analyses can lead to the acquisition of …
[PDF][PDF] 基于可变形卷积神经网络的遥感影像密集区域车辆检测方法
高鑫， 李慧， 张义， 闫梦龙， 张宗朔， 孙显， 孙皓… - 电子与信息学报, 2018 - jeit.ac.cn
车辆检测是遥感图像分析领域的热点研究内容之一, 车辆目标的智能提取和识别, 对于交通管理,
城市建设有重要意义. 在遥感领域中, 现有基于卷积神经网络的车辆检测方法存在实现过程复杂 …
城市建设有重要意义. 在遥感领域中, 现有基于卷积神经网络的车辆检测方法存在实现过程复杂 …
[HTML][HTML] 基于FCNN 和ICAE 的SAR 图像目标识别方法
喻玲娟， 王亚东， 谢晓春， 林赟， 洪文 - 雷达学报, 2018 - radars.ac.cn
近年来, 基于卷积神经网络(Convolutional Neural Network, CNN) 的合成孔径雷达(Synthetic
Aperture Radar, SAR) 图像目标识别得到深入研究. 全卷积神经网络(Fully Convolutional …
Aperture Radar, SAR) 图像目标识别得到深入研究. 全卷积神经网络(Fully Convolutional …
Vehicle detection in remote sensing images of dense areas based on deformable convolution neural network
Vehicle detection is one of the hotspots in the field of remote sensing image analysis. The
intelligent extraction and identification of vehicles are of great significance to traffic …
intelligent extraction and identification of vehicles are of great significance to traffic …
Seismic attribute fusion technology based on SSAE
S ZHOU, H ZHONG - Progress in Geophysics, 2024 - en.dzkx.org
Seismic attribute is a comprehensive reflection of the underground medium and don't simply
coincide with geological targets. Which leads to the inevitable existence of multiple solutions …
coincide with geological targets. Which leads to the inevitable existence of multiple solutions …
基于改进SE-Net 和深度可分离残差的高光谱图像分类
王燕， 王振宇 - 兰州理工大学学报, 2024 - journal.lut.edu.cn
针对目前常见的用于高光谱图像分类的卷积神经网络参数数量多, 训练时间长,
对样本数量依赖性大的问题, 提出一种适用于有限训练样本条件下基于改进压缩激活网络和深度 …
对样本数量依赖性大的问题, 提出一种适用于有限训练样本条件下基于改进压缩激活网络和深度 …
[PDF][PDF] Hyperspectral image classification based on improved SE-Net anddepth-separable residuals
W Yan, W Zhen-yu - Journal of Lanzhou University of Technology, 2024 - journal.lut.edu.cn
In response to the challenges posed by convolutional neural network (CNNs) commonly
used for hyperspectral image classification, namely, their high parameter count, extended …
used for hyperspectral image classification, namely, their high parameter count, extended …
SAR ATR Based on FCNN and ICAE
Y Lingjuan, W Yadong, X Xiaochun, L Yun, H Wen - 雷达学报, 2018 - radars.ac.cn
Abstract In recent years, Synthetic Aperture Radar (SAR) image target recognition based on
the Convolutional Neural Network (CNN) has attracted a significant amount of attention …
the Convolutional Neural Network (CNN) has attracted a significant amount of attention …