Grape maturity estimation based on seed images and neural networks

被引：10

作者：

Zuniga, Alex ^{[3
]}

Mora, Marco ^{[1
,3
]}

Oyarce, Miguel ^{[3
]}

Fredes, Claudio ^{[2
,3
]}

机构：

[1] Univ Catolica Maule, Dept Comp Sci, Santiago, Chile

[2] Univ Catolica Maule, Dept Comp Sci, Santiago, Chile

[3] Univ Catolica Maule, Lab Technol Res Patter Recognit, Santiago, Chile

来源：

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE | 2014年 / 35卷

关键词：

Grape maturity estimation; Neural networks; Appearance descriptors; Seed images; PHENOLIC MATURITY;

D O I：

10.1016/j.engappai.2014.06.007

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The grape phenolic maturity is one of the most important parameters to determine the optimal time for harvest. In this paper we propose an innovative methodology for the problem of how this task is performed today. In particular, the method consists in analyzing seed images using pattern recognition methodology, and classifying them in immature, mature and over mature states through a supervised learning neural network. The methodology presented gives objective information about maturity, which is useful for deciding the moment when the harvest should be performed. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：95 / 104

页数：10

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