Deep learning based automatic grading of bi-colored apples using multispectral images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-022-12230-6.pdf
Reference55 articles.
1. Alam MN, Ullah I, Al-Absi AA (2020) Deep learning-based apple defect detection with residual squeezenet. In: International conference on smart computing and cyber security: strategic foresight, security challenges and innovation. Springer, pp 127–134
2. Anonymous (2004) Commission regulation (ec) no 85/2004 of 15 january 2004 on marketing standards for apples. Off J Eur Union L 13:3–18
3. Ariana D, Guyer DE, Shrestha B (2006) Integrating multispectral reflectance and fluorescence imaging for defect detection on apples. Comput Electron Agric 50(2):148–161
4. Bhatt AK, Pant D (2015) Automatic apple grading model development based on back propagation neural network and machine vision, and its performance evaluation. Ai Soc 30(1):45–56
5. Cheng X, Tao Y, Chen YR, Luo Y (2003) Nir/mir dual-sensor machine vision system for online apple stem-end/calyx recognition. Trans ASAE 46:551–558
Cited by 8 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. Advancements in machine visions for fruit sorting and grading: A bibliometric analysis, systematic review, and future research directions;Journal of Agriculture and Food Research;2024-06
2. Multi-class segmentation of navel orange surface defects based on improved DeepLabv3+;Journal of Agricultural Engineering;2024-02-20
3. Apple Varieties Classification Using Deep Features and Machine Learning;Agriculture;2024-02-03
4. Early Bruise Detection in Apple Based on an Improved Faster RCNN Model;Horticulturae;2024-01-20
5. A robust rice yield estimation framework developed by grading modeling and normalized weight decision-making strategy using UAV imaging technology;Computers and Electronics in Agriculture;2023-12
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