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Yingyue Su

As seen in: MDPI
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Articles

Extraction and Mapping of Cropland Parcels in Typical Regions of Southern China Using Unmanned Aerial Vehicle Multispectral Images and Deep Learning

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By Shikun Wu, Yingyue Su, Xiaojun Lu, Han Xu
| MDPI
2.4. Deep Learning Algorithms U-Net-based CNN algorithms Since the U-Net-based convolutional neural network (CNN) has been proven to obtain better extraction results with limited training samples, this study utilized the U-Net model as the basis for the experiments. The U-Net model (Figure 4a) is an end-to-end network model proposed by Ronneberger et al. for image segmentation [57].
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Remote Sensing | Free Full-Text | Monitoring Cropland Abandonment in Southern China from 1992 to 2020 Based on the Combination of Phenological and Time-Series Algorithm Using Landsat Imagery and Google Earth Engine

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By Han Xu, Yingyue Su, Shikun Wu, Shanggui Kang
| MDPI
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
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