Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques-Reference-Cited by-同舟云学术

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Unlocking plant secrets: A systematic review of 3D imaging in plant phenotyping techniques

Published:2024-07 Issue: Volume:222 Page:109033
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Akhtar Muhammad Salman,Zafar Zuhair,Nawaz Raheel,Fraz Muhammad Moazam^ORCID

Publisher

Elsevier BV

Reference140 articles.

1. MULTINET: A multi-agent DRL and EfficientNet assisted framework for 3D plant leaf disease identification and severity quantification;Allaoua Chelloug;IEEE Access,2023

2. Robust surface reconstruction of plant leaves from 3D point clouds;Ando;Plant Phenom.,2021

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

4. Translating high-throughput phenotyping into genetic gain;Araus;Trends Plant Sci.,2018

5. Field-based robotic phenotyping of sorghum plant architecture using stereo vision;Bao;J. Field Robotics,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Multimodal and Temporal Network-Based Yield Assessment Method for Different Heat-Tolerant Genotypes of Wheat;Agronomy;2024-08-01

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