.png){kind=icon}
返回
Distillation Remote Sensing Object Counting via Multi-Scale Context Feature Aggregation
.png){kind=icon}
PRE
AI
DOI：10.1109/TGRS.2021.3125249.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Remote sensing object counting is an important issue in remote sensing analysis. Remote sensing object counting has many challenges, such as large-scale variations and complex backgrounds. The previous counting methods have many shortboards, such as only focusing on local appearance features of target scenes and ignoring the self-supervision ability of the network itself. To remedy the above problems, in this article, we propose a novel remote sensing object counting method, which contains the adaptive multi-scale context aggregation module (AMCAM) and the self-context distillation module (SCDM). The AMCAM can model and fuse context information from different receptive fields effectively. It also keeps detailed information through multiple pixel attention (PA) modules step by step. The SCDM can improve the representation learning without adding any additional supervision information. SCDM uses feature maps from the deeper layer of the network to supervise feature maps from the earlier layer of the network. Our method has achieved good performance on the remote sensing object counting dataset, RSOC, and mainstream crowd counting datasets, such as ShanghaiTech and UCF-QNRF datasets.
Keyword:
Remote sensing
Convolution
Task analysis
Context modeling
Adaptation models
Deep learning
Sensors
Context information modeling
crowd counting
knowledge distillation
localization
remote sensing object counting
期刊
IF:
8.6
论文数:
2.1W
被引数:
10.7W
机构
引用论文
Caw’s Walking State Recognition Based on Accelerometers and Gyroscopes Installed on Ear-Tags and Collar-Tags基于安装在耳标和项圈上的加速度计和陀螺仪的Caw步行状态识别
PREAI
分享收藏Symplectic Principal Component Analysis: A New Method for Time Series Analysis辛主成分分析: 一种新的时间序列分析方法
OAAI
OAAI分享收藏Electrochemically assisted micro localized grafting of aptamers in a microchannel engraved in fluorinated thermoplastic polymer Dyneon THV.png)
RSC Advances
RSC AdvancesIF0
PREAI
分享收藏
查看更多内容