Assessment of grapevine variety discrimination using stem hyperspectral data and AdaBoost of random weight neural networks-Reference-Cited by-同舟云学术

Assessment of grapevine variety discrimination using stem hyperspectral data and AdaBoost of random weight neural networks

Published:2018-11 Issue: Volume:72 Page:140-155
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Fernandes Armando,Utkin Andrei,Eiras-Dias José,Silvestre José,Cunha Jorge,Melo-Pinto Pedro

Publisher

Elsevier BV

Subject

Software

Reference39 articles.

1. Characterization of grapevines by the use of genetic markers;Tomic,2013

2. Non-destructive discrimination of Chinese bayberry varieties using Vis/NIR spectroscopy;Li;J. Food Eng.,2007

3. On-site variety discrimination of tomato plant using visible-near infrared reflectance spectroscopy;Xu;J. Zhejiang Univ. Sci. B,2009

4. Boosting partial least-squares discriminant analysis with application to near infrared spectroscopic tea variety discrimination: BPLS-DA for NIR tea variety discrimination;Tan;J. Chemom.,2012

5. Rapid and non-destructive discrimination of tea varieties by near infrared diffuse reflection spectroscopy coupled with classification and regression trees;Tan;Afr. J. Biotechnol.,2012

Cited by 12 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. Object Detection and Recognition Techniques Based on Digital Image Processing and Traditional Machine Learning for Fruit and Vegetable Harvesting Robots: An Overview and Review;Agronomy;2023-02-23

2. RGB images-driven recognition of grapevine varieties using a densely connected convolutional network;Logic Journal of the IGPL;2022-02-16

3. White grape quality monitoring via hyperspectral imaging: from the vineyard to the winery;White Wine Technology;2022

4. Artificial Intelligence and Big Data Analytics in Vineyards: A Review;Grapes and Wine [Working Title];2021-08-26

5. RGB Images Driven Recognition of Grapevine Varieties;Advances in Intelligent Systems and Computing;2020-08-29