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...
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: | |
Online Access: | https://www.mdpi.com/2072-4292/12/10/1668 |
Similar Items
-
Mapping of plastic greenhouses and mulching films from very high resolution remote sensing imagery based on a dilated and non-local convolutional neural network
by: Quanlong Feng, et al.
Published: (2021-10-01) -
An Efficient Detection Approach for Unmanned Aerial Vehicle (UAV) Small Targets Based on Group Convolution
by: Jianghao Cheng, et al.
Published: (2022-05-01) -
Spatio-Temporal Analysis of Ground Movement Using Unmanned Aerial Vehicle Photogrammetry in Gampong Lamkleng, Aceh Besar
by: Nabila Amalia, et al.
Published: (2023-06-01) -
An Attention-Based Convolutional Recurrent Neural Networks for Scene Text Recognition
by: Adil Abdullah Abdulhussein Alshawi, et al.
Published: (2024-01-01) -
Mathematical Modelling of Unmanned Aerial Vehicles
by: Saeed Sarwar, et al.
Published: (2013-04-01)