Toward Hierarchical Adaptive Alignment for Aerial Object Detection in Remote Sensing Images-Reference-Cited by-同舟云学术

Toward Hierarchical Adaptive Alignment for Aerial Object Detection in Remote Sensing Images

Published:2023 Issue: Volume:61 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Deng Chenwei¹^ORCID,Jing Donglin¹,Han Yuqi¹^ORCID,Chanussot Jocelyn²^ORCID

Affiliation:

1. Beijing Key Laboratory of Embedded Real-Time Information Processing Technique, School of Information and Electronics, Beijing Institute of Technology, Beijing, China

2. Grenoble INP GIPSA-Lab, CNRS, Université Grenoble Alpes, Grenoble, France

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10180012.pdf?arnumber=10180012

Reference65 articles.

1. You Only Look Once: Unified, Real-Time Object Detection

2. A Novel Nonlocal-Aware Pyramid and Multiscale Multitask Refinement Detector for Object Detection in Remote Sensing Images

3. Arbitrary-Oriented Ship Detection Framework in Optical Remote-Sensing Images

4. Rotation-aware and multi-scale convolutional neural network for object detection in remote sensing images

5. Target Detection Model Distillation Using Feature Transition and Label Registration for Remote Sensing Imagery

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