孵化
分类器(UML)
遗传算法
人工智能
拉曼光谱
管道(软件)
计算机科学
算法
生物
机器学习
动物科学
物理
光学
程序设计语言
作者
Ünsal Gökdağ,Esra Çınar
标识
DOI:10.1109/siu.2018.8404337
摘要
Early (Pre-hatch) gender classification of fertilized avian eggs is an important industrial and ethical problem as male chicks are manually identified and terminated after hatching in routine egg production pipeline. The chemical composition of male and female eggs are known to differentiate, yet there is no nondestructive method deployed. We propose to analyze the chemical combination of fertilized eggs by means of Raman spectroscopy. A genetic algorithm based classifier is trained and tested on a sample of 20 eggs. Preliminary results suggest the feasibility of the proposed method in industrial applications.
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