A novel deep <scp>learning‐based</scp> method for detection of weeds in vegetables-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A novel deep learning‐based method for detection of weeds in vegetables

Published:2022-02-02 Issue:5 Volume:78 Page:1861-1869
ISSN:1526-498X
Container-title:Pest Management Science
language:en
Short-container-title:Pest Management Science

Author:

Jin Xiaojun¹^ORCID,Sun Yanxia²,Che Jun¹,Bagavathiannan Muthukumar³^ORCID,Yu Jialin³⁴^ORCID,Chen Yong¹

Affiliation:

1. College of Mechanical and Electronic Engineering Nanjing Forestry University Nanjing China

2. School of Rail Transportation Nanjing Vocational Institute of Transport Technology Nanjing China

3. Department of Soil and Crop Sciences Texas A&M University College Station TX USA

4. College of Forestry Nanjing Forestry University Nanjing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Insect Science,Agronomy and Crop Science,General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ps.6804

Reference72 articles.

1. World vegetable industry: production, breeding, trends;Ryder E;Hortic Rev,2011

2. Acidification and salinization of soils with different initial pH under greenhouse vegetable cultivation

3. Analysis of the variability of pesticide concentration downstream of inline mixers for direct nozzle injection systems

4. Weed Detection for Selective Spraying: a Review

5. A survey of image processing techniques for plant extraction and segmentation in the field

Cited by 75 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. Development and evaluation of a machine vision and deep learning-based smart sprayer system for site-specific weed management in row crops: An edge computing approach;Journal of Agriculture and Food Research;2024-12

2. Field-based multispecies weed and crop detection using ground robots and advanced YOLO models: A data and model-centric approach;Smart Agricultural Technology;2024-12

3. Lightweight cabbage segmentation network and improved weed detection method;Computers and Electronics in Agriculture;2024-11

4. A comprehensive survey on weed and crop classification using machine learning and deep learning;Artificial Intelligence in Agriculture;2024-09

5. Integration of Remote Sensing and Machine Learning for Precision Agriculture: A Comprehensive Perspective on Applications;Agronomy;2024-09-01

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3