Automated fruit grading using optimal feature selection and hybrid classification by self-adaptive chicken swarm optimization: grading of mango
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-021-06473-x.pdf
Reference48 articles.
1. Arun Kumar R, Rajpurohit VS, Bidari KY (2019) Multi class grading and quality assessment of pomegranate fruits based on physical and visual parameters. Int J Fruit Sci 19(4):372–396
2. Castro W, Oblitas J, De-La-Torre M, Cotrina C, Bazán K, Avila-George H (2019) Classification of cape gooseberry fruit according to its level of ripeness using machine learning techniques and different color spaces. IEEE Access 7:27389–27400
3. Kaur H, Sawhney BK, Jawandha SK (2018) Evaluation of plum fruit maturity by image processing techniques. J Food Sci Technol 55:3008–3015
4. Nasiri A, Taheri-Garavand A, Zhang Y-D (2019) Image-based deep learning automated sorting of date fruit. Postharvest Biol Technol 153:133–141
5. Ren A et al (2020) Machine learning driven approach towards the quality assessment of fresh fruits using non-invasive sensing. IEEE Sens J 20(4):2075–2083
Cited by 15 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. Improved hybrid feature extractor in lightweight convolutional neural network for postharvesting technology: automated oil palm fruit grading;Neural Computing and Applications;2024-08-12
2. A grader for fresh jujube with electromagnetic synchronous actuator assembly;Journal of Food Process Engineering;2024-07
3. A VGG-CHNN Model for Identifying and Categorizing Diseases through Transfer Learning on Mango Images;2023 4th International Conference on Intelligent Technologies (CONIT);2024-06-21
4. A comprehensive survey on the chicken swarm optimization algorithm and its applications: state-of-the-art and research challenges;Artificial Intelligence Review;2024-06-11
5. AI&ML-based smart non-disruptive methods for post-harvest fruit grading: State-of-the-Art;2024 MIT Art, Design and Technology School of Computing International Conference (MITADTSoCiCon);2024-04-25
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