Crop Identification of UAV Images Based on an Unsupervised Semantic Segmentation Method-Reference-Cited by-同舟云学术

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Crop Identification of UAV Images Based on an Unsupervised Semantic Segmentation Method

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Zhang Zebing¹,Wang Leiguang²^ORCID,Chen Yuncheng¹,Zheng Chen³^ORCID

Affiliation:

1. School of Mathematics and Statistics, Henan University, Kaifeng, China

2. School of Biodiversity Conservation, Southwest Forestry University, Kunming, China

3. School of Mathematics and Statistics and the Henan Engineering Research Center for Artificial Intelligence Theory and Algorithms, Henan University, Kaifeng, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Henan

Scientific and Technological Innovation Talent in Universities of Henan Province

Youth Key Teacher of Henan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10433183.pdf?arnumber=10433183

Reference19 articles.

1. A Self-Learning-Update CNN Model for Semantic Segmentation of Remote Sensing Images

2. High-Order Semantic Decoupling Network for Remote Sensing Image Semantic Segmentation

3. Semantic Segmentation of Remote-Sensing Images Through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models

4. PolSAR Image Classification Based on Object-Based Markov Random Field With Polarimetric Auxiliary Label Field

5. Identification of Mangrove Invasive Plant Derris Trifoliate Using UAV Images and Deep Learning Algorithms

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