Reducing False Detections in Aerial Images by Exploiting the Context Information and Centroid Relationship-Reference-Cited by-同舟云学术

Reducing False Detections in Aerial Images by Exploiting the Context Information and Centroid Relationship

Published:2022 Issue: Volume:71 Page:1-14
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Yang Yang¹^ORCID,Zang Bingjie¹^ORCID,Li Nan²^ORCID,Zhao Boya³^ORCID,Li Beichen¹^ORCID,Lang Yue⁴^ORCID

Affiliation:

1. School of Electrical and Information Engineering, Tianjin University, Tianjin, China

2. Shenzhen Institute of Artificial Intelligence and Robotics for Society and the Institute of Robotics and Intelligent Manufacturing, The Chinese University of Hong Kong, Shenzhen, Shenzhen, China

3. Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

4. School of Electronic and Information Engineering, Hebei University of Technology, Tianjin, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09812732.pdf?arnumber=9812732

Reference63 articles.

1. Focal Loss for Dense Object Detection

2. DetNet: Design Backbone for Object Detection

3. Learning Rotation-Invariant and Fisher Discriminative Convolutional Neural Networks for Object Detection

4. Deep learning for hyperspectral imagery classification: The state of the art and prospects;zhang;ACTA Automatica Sinica,2018

5. Learning Rotation-Invariant Convolutional Neural Networks for Object Detection in VHR Optical Remote Sensing Images

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Small Object Detection in Remote Sensing Images Based on Redundant Feature Removal and Progressive Regression;IEEE Transactions on Geoscience and Remote Sensing;2024