YOLO-WDNet: A lightweight and accurate model for weeds detection in cotton field-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

YOLO-WDNet: A lightweight and accurate model for weeds detection in cotton field

Published:2024-10 Issue: Volume:225 Page:109317
ISSN:0168-1699
Container-title:Computers and Electronics in Agriculture
language:en
Short-container-title:Computers and Electronics in Agriculture

Author:

Fan Xiangpeng,Sun Tan,Chai Xiujuan,Zhou Jianping

Funder

Beijing University of Agriculture

China Postdoctoral Science Foundation

National Key Clinical Specialty Discipline Construction Program of China

Natural Science Foundation of Beijing Municipality

Qingdao Postdoctoral Science Foundation

Beijing Natural Science Foundation

Zhejiang Academy of Agricultural Sciences

Publisher

Elsevier BV

Reference38 articles.

1. Performance of deep learning models for classifying and detecting common weeds in corn and soybean production systems;Ahmad;Comput. Electron. Agric.,2021

2. Classification of weed using machine learning techniques: a review—challenges, current and future potential techniques;Al-Badri;J. Plant Dis. Prot.,2022

3. A review of advanced machine learning methods for the detection of biotic stress in precision crop protection;Behmann;Precis. Agric.,2015

4. Agroavnet for crops and weeds classification: a step forward in automatic farming;Chavan;Comput. Electron. Agric.,2018

5. Weed detection in sesame fields using a yolo model with an enhanced attention mechanism and feature fusion;Chen;Comput. Electron. Agric.,2022

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