NDLI: Pattern recognition system of Jatropha curcas fruits using back propagation

Content Provider	IEEE Xplore Digital Library
Author	Effendi, Z. Ramli, R. Ghani, J.A. Rahman, M.N.A.
Copyright Year	2009
Description	Author affiliation: Dept. of Mechanical and Materials Engineering, Faculty of Engineering, 34600 UKM Bangi, Selangor, Malaysia (Effendi, Z.; Ramli, R.; Ghani, J.A.; Rahman, M.N.A.)
Abstract	Jatropha curcas has been widely accepted as a favorite agricultural solution for all subtropical and tropical that can produce high quantity and quality feedstock for bio energy. Jatropha curcas oil as biodiesel feedstock has a bright prospective because it is categorized as non edible oil which the availability will not be threaten by food purposes. Traditional identification of Jatropha curcas fruits is performed by human experts. The Jatropha curcas fruit quality depends on type and size of defects as well as skin color and fruit size. This research develops a pattern recognition system to identify the Jatropha curcas fruit maturity and grade the fruit into relevant quality category. The system is divided into two stages: the first stage is a training stage that is to extract the characteristics from the pattern. The second stages is to recognize the pattern by using the characteristics derived from the first task. Back propagation diagnosis model is used to recognition the Jatropha curcas fruits. It is ascertained for the developed system is used in recognizing the maturity of Jatropha curcas fruits. This paper presents a pattern recognition system of Jatropha curcas using back propagation.
Starting Page	58
Ending Page	62
File Size	871568
Page Count	5
File Format	PDF
ISBN	9781424455607
e-ISBN	9781424455614
DOI	10.1109/ICSIPA.2009.5478719
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-11-18
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Image processing Pattern recognition Agricultural engineering Biofuels Petroleum Neural Network Pattern Recognition Image color analysis Neural networks Back Jatropha curcas Fruit Power engineering and energy
Content Type	Text
Resource Type	Article

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