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040			_cCvSU Main Campus Library
041	0		_aeng
082	0	4	_a621.367 _bB96 2022
100			_aBustamante, Mariel G. _936775 _eauthor
245	1	0	_aDesign and development of aroid plant defect classifier using convolutional neural network / _cby Mariel G. Bustamante and Jacob D. Mojares.
260			_aIndang, Cavite : _bCavite State University- Main Campus, _c2022.
300			_axv, 72 pages : _billustrations ; _c28 cm
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
500			_aDesign Project (Bachelor of Science in Electronics and Communications Engineering) Cavite State University.
504			_aIncludes bibliographical references.
508			_aCollege of Engineering and Information Technology (CEIT)
520	3		_aBUSTAMANTE, MARIEL G., and MOJARES, JACOB D. Design and Development of Aroid Plant Defect Classifier using Convolutional Neural Network. Undergraduate Design Project. Bachelor of Science in Electronics Engineering. Cavite State University, Indang, Cavite. August 2022. Adviser: Dr. Edwin R. Arboleda. The general objective of the study was to design and develop an Aroid Plant Defect Classifier using Convolutional Neural Network. It was intended to be portable and rechargeable. It was targeted to be capable of classifying defects of a Black Velvet "Alocasia reginula" plant based on its leaves to avoid severe damage due to improper watering. The design project was composed of Raspberry Pi 3B+ which handled all the processes the device had to execute. This microcomputer was used to interface other components of the device such as the Camera, Battery, and Touchscreen Display. The back-end system of this device was a trained Convolutional Neural Network Model with an Accuracy of 89.50% while the front-end system was a Graphical User Interface displayed on the Touchscreen display when it turned ON. The project was tested by the researchers at a farm in Dasmariñas, Cavite, where the device had accuracy values of 90.48%, 87.62%, and 91.43%, and precision values of 87.88%, 78.75%, and 88.24% in classifying Normal, Underwatered, and Overwatered leaves, respectively, using a confusion matrix. The evaluation was conducted at the Engineering Science Building, Cavite State University, Indang, Cavite with the Electronics Engineer Professors. Based on the results of the evaluation, the design project succeeded in achieving its objectives. The overall performance was considered satisfactory. The cost of the construction of the system amounted to P11,176.00.
541			_cSubmitted to the University Library _d09/01/2022 _eDP-753
650		0	_aImage processing _91174
650		0	_aImage processing software _919368
690			_aBachelor of Science in Electronics and Communications Engineering _94922
700			_aMojares, Jacob D. _eauthor _936779
700			_aArboleda, Edwin R. _eadviser _94719
856			_p80 _yClick here to view the Abstract and Table of Contents _uhttp://library.cvsu.edu.ph/cgi-bin/koha/opac-retrieve-file.pl?id=699ae8c4282d568d6899cfb0e7dc5e46
942			_2ddc _cMAN
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