Balanced Density Regression Network for Remote Sensing Object Counting-Reference-Cited by-同舟云学术

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Balanced Density Regression Network for Remote Sensing Object Counting

Published:2024 Issue: Volume:62 Page:1-13
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Guo Haojie¹^ORCID,Gao Junyu¹^ORCID,Yuan Yuan¹^ORCID

Affiliation:

1. School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China

Funder

National Science Fund for Distinguished Young Scholars

National Key Research and Development Project

Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10535416.pdf?arnumber=10535416

Reference68 articles.

1. Object Counting for Remote-Sensing Images via Adaptive Density Map-Assisted Learning

2. SSRNet: In-Field Counting Wheat Ears Using Multi-Stage Convolutional Neural Network

3. Remote Sensing Object Counting Through Regression Ensembles and Learning to Rank

4. An Anchor-Free Network With Density Map and Attention Mechanism for Multiscale Object Detection in Aerial Images

5. Vehicle Counting in Very Low-Resolution Aerial Images via Cross-Resolution Spatial Consistency and Intraresolution Time Continuity

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