Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery-Reference-Cited by-同舟云学术

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Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery

Published:2024-02 Issue:2 Volume:9 Page:1708-1715
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Li Qi¹^ORCID,Cai Jiaxin¹^ORCID,Luo Jiexin¹^ORCID,Yu Yuanlong¹^ORCID,Gu Jason²^ORCID,Pan Jia³^ORCID,Liu Wenxi¹^ORCID

Affiliation:

1. College of Computer and Data Science, Fuzhou University, Fuzhou, China

2. Department of Electrical and Computer Engineering, Dalhousie University, Halifax, NS, Canada

3. Department of Computer Science, University of Hong Kong, Hong Kong, SAR, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7083369/10360389/10380673.pdf?arnumber=10380673

Reference51 articles.

1. GPS-Denied UAV Localization using Pre-existing Satellite Imagery

2. Air-to-Air Visual Detection of Micro-UAVs: An Experimental Evaluation of Deep Learning

3. Fast Classification of Large Germinated Fields Via High-Resolution UAV Imagery

4. Large Scale Image Mosaic Construction for Agricultural Applications

5. Binary Neural Networks for Memory-Efficient and Effective Visual Place Recognition in Changing Environments

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1. RTMDet-MGG: A Multi-Task Model With Global Guidance;IEEE Transactions on Intelligent Transportation Systems;2024

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