A dual-path model merging CNN and RNN with attention mechanism for crop classification

Author:

Zhang Fuyao,Yin Jielin,Wu Nan,Hu Xinyu,Sun Shikun,Wang Yubao

Funder

National Natural Science Foundation of China

Project 211

Publisher

Elsevier BV

Reference41 articles.

1. A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach;Cai;Remote Sens. Environ.,2018

2. A joint learning Im-BiLSTM model for incomplete time-series Sentinel-2A data imputation and crop classification;Chen;Int. J. Appl. Earth Obs. Geoinf.,2022

3. Annual maps of global artificial impervious area (GAIA) between 1985 and 2018;Gong;Remote Sens. Environ.,2020

4. Google Earth Engine: Planetary-scale geospatial analysis for everyone;Gorelick;Remote Sens. Environ.,2017

5. Improved Gaussian mixture model to map the flooded crops of VV and VH polarization data;Guan;Remote Sens. Environ.,2023

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