Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Beijing Academy of Agricultural and Forestry Sciences
Subject
Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry
Reference76 articles.
1. Sentinel SAR-optical fusion for crop type mapping using deep learning and Google Earth Engine;Adrian;ISPRS J. Photogramm. Remote Sens.,2021
2. Bailly, S., Giordano, S., Landrieu, L., Chehata, N., 2018. Crop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping. In: Proc. of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
3. Effects of sample size and network depth on a deep learning approach to species distribution modeling;Benkendorf;Eco. Inform.,2020
4. Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture;Bosilj;J. Field Rob.,2019
5. Chughtai, A.H., Abbasi, H., Karas, I.R., 2021. A review on change detection method and accuracy assessment for land use land cover. Rem. Sens. Appl.: Soc. Environ. 22.