Multi-Temporal Unmanned Aerial Vehicle Remote Sensing for Vegetable Mapping Using an Attention-Based Recurrent Convolutional Neural Network

Multi-Temporal Unmanned Aerial Vehicle Remote Sensing for Vegetable Mapping Using an Attention-Based Recurrent Convolutional Neural Network

Vegetable mapping from remote sensing imagery is important for precision agricultural activities such as automated pesticide spraying. Multi-temporal unmanned aerial vehicle (UAV) data has the merits of both very high spatial resolution and useful phenological information, which shows great potentia...

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Bibliographic Details
Main Authors: Quanlong Feng, Jianyu Yang, Yiming Liu, Cong Ou, Dehai Zhu, Bowen Niu, Jiantao Liu, Baoguo Li
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Remote Sensing
Subjects:
vegetable mapping
multi-temporal UAV
recurrent convolutional neural network
attention mechanism
Online Access:https://www.mdpi.com/2072-4292/12/10/1668

Internet

https://www.mdpi.com/2072-4292/12/10/1668

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