Development of image-based wheat spike counter through a Faster R-CNN algorithm and application for genetic studies-Reference-Cited by-同舟云学术

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Development of image-based wheat spike counter through a Faster R-CNN algorithm and application for genetic studies

Published:2022-10 Issue:5 Volume:10 Page:1303-1311
ISSN:2214-5141
Container-title:The Crop Journal
language:en
Short-container-title:The Crop Journal

Author:

Li Lei,Hassan Muhammad Adeel,Yang Shurong,Jing Furong,Yang Mengjiao,Rasheed Awais,Wang Jiankang,Xia Xianchun,He Zhonghu,Xiao Yonggui

Publisher

Elsevier BV

Subject

Plant Science,Agronomy and Crop Science

Reference43 articles.

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

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

3. Using neural network to identify the severity of wheat Fusarium head blight in the field environment;Zhang;Remote Sens.,2019

4. An automated, high-throughput plant phenotyping system using machine learning based plant segmentation and image analysis;Lee;PLoS ONE,2018

5. An automatic method for stomatal pore detection and measurement in microscope images of plant leaf based on a convolutional neural network model;Song;Forests,2020

Cited by 28 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. Detection of rice panicle density for unmanned harvesters via RP-YOLO;Computers and Electronics in Agriculture;2024-11

2. Real-Time Detection and Counting of Wheat Spikes Based on Improved YOLOv10;Agronomy;2024-08-28

3. Modern phenomics to empower holistic crop science, agronomy, and breeding research;Journal of Genetics and Genomics;2024-08

4. YOLO-LF: a lightweight multi-scale feature fusion algorithm for wheat spike detection;Journal of Real-Time Image Processing;2024-08

5. Artificial intelligence in plant breeding;Trends in Genetics;2024-08

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