A novel and proposed comprehensive methodology using deep convolutional neural networks for flue cured tobacco leaves classification-Reference-Cited by-同舟云学术

A novel and proposed comprehensive methodology using deep convolutional neural networks for flue cured tobacco leaves classification

Published:2018-05-04 Issue:1 Volume:11 Page:107-117
ISSN:2511-2104
Container-title:International Journal of Information Technology
language:en
Short-container-title:Int. j. inf. tecnol.

Author:

Dasari Siva Krishna,Prasad Vadamodula

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Information Systems

Link

http://link.springer.com/article/10.1007/s41870-018-0174-4/fulltext.html

Reference28 articles.

1. CTRI-Rajahmundry (2015) Tobacco in Indian economy. http://www.ctri.org.in/fortobaccoEconomy.php

2. China Tobacco Corporation (1992) Training handbook of Chinese grading criteria of flue-cured tobacco leaves. China Standards Publishing House, Beijing, pp 1–38

3. United States Department of Agriculture Official Standard Grades for Flue-Cured Tobacco (1989) U.S. Types 11, 12, 13, 14, and Foreign Type 92, 27 March 1989

4. Zhang J et al (1997) A trainable grading system for tobacco leaves. Comput Electron Agric 16(3):231–244

5. Han L (2008) Recognition of the part of growth of fluecured tobacco leaves based on support vector machine. In: Intelligent Control and Automation, WCICA 2008. IEEE 7th World Congress on 2008, pp 3624–3627

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