Multimodal Deep Learning for Rice Yield Prediction Using UAV-Based Multispectral Imagery and Weather Data

Multimodal Deep Learning for Rice Yield Prediction Using UAV-Based Multispectral Imagery and Weather Data

Precise yield predictions are useful for implementing precision agriculture technologies and making better decisions in crop management. Convolutional neural networks (CNNs) have recently been used to predict crop yields in unmanned aerial vehicle (UAV)-based remote sensing studies, but weather data...

Full description

Bibliographic Details
Main Authors: Md. Suruj Mia, Ryoya Tanabe, Luthfan Nur Habibi, Naoyuki Hashimoto, Koki Homma, Masayasu Maki, Tsutomu Matsui, Takashi S. T. Tanaka
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Remote Sensing
Subjects:
convolutional neural network
heading stage
model depth
remote sensing
within-field variability
Online Access:https://www.mdpi.com/2072-4292/15/10/2511

Internet

https://www.mdpi.com/2072-4292/15/10/2511

Similar Items