Fruit Classification Using Traditional Machine Learning and Deep Learning Approach
Author:
Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-37218-7_10
Reference16 articles.
1. Kamilaris, A., Prenafeta-boldú, F.X.: Deep learning in agriculture: a survey. Comput. Electron. Agric. 147, 70–90 (2018)
2. Dimatira, J.B.U., Dadios, E.P., Culibrina, F., et al.: Application of fuzzy logic in recognition of tomato fruit maturity in smart farming. In: IEEE Region 10 Annual International Conference, Proceedings/TENCON, pp. 2031–2035 (2017)
3. Zhang, Y., Wang, S., Ji, G., Phillips, P.: Fruit classification using computer vision and feedforward neural network. J. Food Eng. 143, 167–177 (2014)
4. Zhang, Y., Wu, L.: Classification of fruits using computer vision and a multiclass support vector machine. Sensors 12, 12489–12505 (2012)
5. Srinivasan, K., Porkumaran, K., Sainarayanan, G.: A new approach for human activity analysis through identification of body parts using skin colour segmentation. Int. J. Signal Imaging Syst. Eng. 3(2), 93–104 (2010)
Cited by 16 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. YOLOv9s-Pear: A Lightweight YOLOv9s-Based Improved Model for Young Red Pear Small-Target Recognition;Agronomy;2024-09-12
2. A System and Method for Fruit Ripeness Prediction Using Transfer Learning and CNN;2024 International Conference on Communication, Computing and Internet of Things (IC3IoT);2024-04-17
3. Android-Based Application for Ripeness Classification and Shelf-Life Determination of Philippine Bananas;2024 2nd International Conference on Computer Graphics and Image Processing (CGIP);2024-01-12
4. Classification of Nitrogen Deficiency in Wheat Crop Images Using Different Machine Learning Approaches with ORANGE Tool;Lecture Notes in Networks and Systems;2024
5. Classification of Rotten Fruits vs Fresh Fruits Using Sequential Model with Convolutional Neural Network;2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS);2023-11-03
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