.png){kind=icon}
返回
Remote Sensing Object Detection Based on Gated Context-Aware Module
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2022.3223069.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Recently, deep learning algorithms, especially feature pyramid network (FPN), have achieved significant progress in object detection of natural scene images. However, due to the complex scenes of remote sensing images and the diversity of remote sensing objects, FPN still faces the following drawback when applied to remote sensing object detection (RSOD). Specifically, in the original FPN, the features of each proposal are extracted by RoIAlign. However, these features have limited effective receptive fields, making FPN lack crucial contextual information to accurately classify and locate objects, as well as filter some background noises that possess similar appearance with objects. To alleviate the above problem, in this letter, we propose a gated context-aware module (G-CAM) and replace the original RoIAlign in FPN with the proposed G-CAM to adaptively incorporate the useful local context surrounding each proposal and the global context of the whole image into FPN, enabling FPN to effectively detect objects in remote sensing images. Extensive experiments have been conducted on the object detection in optical remote sensing images (DIOR) and RSOD datasets, which validates that the proposed method achieves superior performance to the considered state-of-the-art methods in terms of detection accuracy.
Keyword:
Convolutional neural networks (CNNs)
gated context-aware module (G-CAM)
object detection
remote sensing
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
CDD-Net: A Context-Driven Detection Network for Multiclass Object DetectionCdd-net: 用于多类对象检测的上下文驱动检测网络
PREAI
分享收藏Thermal comfort, perceived air quality, and cognitive performance when personally controlled air movement is used by tropically acclimatized persons当热带适应的人使用个人控制的空气运动时，热舒适性，感知的空气质量和认知表现.png)
Indoor Air
OAAI
Indoor AirIF0
OAAI分享收藏Object detection in optical remote sensing images: A survey and a new benchmark光学遥感图像中的目标检测: 调查和新基准OAAI
OAAI分享收藏Scenario Context-Aware-Based Bidirectional Feature Pyramid Network for Remote Sensing Target Detection基于场景上下文感知的双向特征金字塔网络遥感目标检测
PREAI
分享收藏CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing ImageryCAD-Net: 遥感图像中对象的上下文感知检测网络OAAI
OAAI分享收藏Cross-Scale Feature Fusion for Object Detection in Optical Remote Sensing Images基于跨尺度特征融合的光学遥感图像目标检测
PREAI
分享收藏
查看更多内容