Application of UAV-Based Imaging and Deep Learning in Assessment of Rice Blast Resistance-Reference-Cited by-同舟云学术

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Application of UAV-Based Imaging and Deep Learning in Assessment of Rice Blast Resistance

Published:2023-11 Issue:6 Volume:30 Page:652-660
ISSN:1672-6308
Container-title:Rice Science
language:en
Short-container-title:Rice Science

Author:

Shaodan Lin,Yue Yao,Jiayi Li,Xiaobin Li,Jie Ma,Haiyong Weng,Zuxin Cheng,Dapeng Ye

Funder

Natural Science Foundation of Fujian Province

Publisher

Elsevier BV

Subject

Plant Science,Agronomy and Crop Science,Biotechnology

Reference30 articles.

1. Application of hyperspectral imaging in the assessment of drought and salt stress in magneto-primed Triticale seeds;Alvarez;Plants,2021

2. Extraction of areas of rice false smut infection using UAV hyperspectral data;An;Remote Sens,2021

3. The origins of the International Rice Research Institute;Anderson;Minerva,1991

4. Field high-throughput phenotyping: The new crop breeding frontier;Araus;Trends Plant Sci,2014

5. Estimation of spinach (Spinacia oleracea) seed yield with 2D UAV data and deep learning;Ariza-Sentís;Smart Agric Technol,2023

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2. Rice breeding for low input agriculture;Frontiers in Plant Science;2024-06-21

3. Efficient Damage Assessment of Rice Bacterial Leaf Blight Disease in Agricultural Insurance Using UAV Data;Agronomy;2024-06-19

4. Design and performance analysis of decision tree learning model for classification of dry and cooked rice samples;European Food Research and Technology;2024-05-07

5. Optimal Relay Algorithm for Unmanned Aerial Vehicles Based on Location Prediction;Proceedings of the 2nd International Conference on Signal Processing, Computer Networks and Communications;2023-12-08

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