Potential of Hybrid CNN-RF Model for Early Crop Mapping with Limited Input Data

When sufficient time-series images and training data are unavailable for crop classification, features extracted from convolutional neural network (CNN)-based representative learning may not provide useful information to discriminate crops with similar spectral characteristics, leading to poor class...

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Autors principals:	Geun-Ho Kwak, Chan-won Park, Kyung-do Lee, Sang-il Na, Ho-yong Ahn, No-Wook Park
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2021-04-01
Col·lecció:	Remote Sensing
Matèries:	crop classification convolution neural networks random forest hybrid model training data time-series images
Accés en línia:	https://www.mdpi.com/2072-4292/13/9/1629
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