CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images

CCTNet: Coupled CNN and Transformer Network for Crop Segmentation of Remote Sensing Images

Semantic segmentation by using remote sensing images is an efficient method for agricultural crop classification. Recent solutions in crop segmentation are mainly deep-learning-based methods, including two mainstream architectures: Convolutional Neural Networks (CNNs) and Transformer. However, these...

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Bibliographic Details
Main Authors: Hong Wang, Xianzhong Chen, Tianxiang Zhang, Zhiyong Xu, Jiangyun Li
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Remote Sensing
Subjects:
semantic segmentation
agricultural research
remote sensing
deep learning
CNN
Transformer
Online Access:https://www.mdpi.com/2072-4292/14/9/1956

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