Abstract
Jinping Liu, Jiayao Wang, Qingfeng Hu
Abstract
Authors
Institutions
Provenance
crossref
Confidence 100%
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Confidence 99%
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Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks
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A source-free unsupervised domain adaptation method for cross-regional and cross-time crop mapping from satellite image time series
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An unsupervised domain adaptation deep learning method for spatial and temporal transferable crop type mapping using Sentinel-2 imagery
10.1016/j.isprsjprs.2023.04.002 · doi-reference
DeepCropMapping: A multi-temporal deep learning approach with improved spatial generalizability for dynamic corn and soybean mapping
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Deep learning based multi-temporal crop classification
10.1016/j.rse.2018.11.032 · doi-reference
Deep Learning Classification of Land Cover and Crop Types Using Remote Sensing Data
10.1109/lgrs.2017.2681128 · doi-reference
Fully Convolutional Networks for Semantic Segmentation
10.1109/tpami.2016.2572683 · doi-reference
Mapping of cropland, cropping patterns and crop types by combining optical remote sensing images with decision tree classifier and random forest
10.1080/10095020.2022.2100287 · doi-reference
10.3390/rs14040829
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Landsat-8 vs. Sentinel-2: Examining the added value of sentinel-2’s red-edge bands to land-use and land-cover mapping in Burkina Faso
10.1080/15481603.2017.1370169 · doi-reference
Mapping weed infestation in maize fields using Sentinel-2 data
10.1016/j.pce.2024.103571 · doi-reference
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Improving crop classification accuracy with integrated Sentinel-1 and Sentinel-2 data: A case study of barley and wheat
10.1007/s41651-023-00152-2 · doi-reference
A deep learning framework for crop mapping with reconstructed Sentinel-2 time series images
10.1016/j.compag.2023.108227 · doi-reference
Challenges and opportunities in remote sensing-based crop monitoring: A review
10.1093/nsr/nwac290 · doi-reference
10.3390/rs14153806
10.3390/rs14153806 · doi-reference
10.3390/app12031670
10.3390/app12031670 · doi-reference
Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data
10.1080/15481603.2019.1650447 · doi-reference
Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks
10.1016/j.neunet.2018.05.019 · doi-reference