ECA-MobileNetV3(Large)+SegNet Model for Binary Sugarcane Classification of Remotely Sensed Images

Author:

Zhou Guoqing1ORCID,Liu Weiguang1ORCID,Zhu Qiang1,Lu Yanling1,Liu Yu2ORCID

Affiliation:

1. College of Geomatics and Geoinformation, Guilin University of Technology, Guilin, China

2. School of Earth and Space Sciences, Peking University, Beijing, China

Funder

National Natural Science of China

Guangxi Innovative Development Grand Program

Guangxi Natural Science Foundation for Innovation Research Team

Guilin Research and Development Plan Program

National Key Research and Development Program of China

BaGuiScholars Program of Guangxi

Open Fund of Guangxi Key Laboratory of Spatial Information and Mapping

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Reference59 articles.

1. Semantic image segmentation with deep convolutional nets and fully connected CRFs;chen;Proc Int Conf Learn Represent,2015

2. Understanding Convolution for Semantic Segmentation

3. Fully Convolutional Networks for Semantic Segmentation

4. Deep Residual Learning for Image Recognition

5. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc ICML,2015

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