| 000 -LEADER |
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| fixed length control field |
02818nam a22003137a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240506195823.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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240506b ||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
|---|
| Language of cataloging |
English. |
| Transcribing agency |
CvSU-CCAT Campus Library. |
| Description conventions |
rda. |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
UM QA 76.87 |
| Item number |
D48 2019 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
De Vega, Justine Carlo, author. |
| 9 (RLIN) |
11926 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
A root crop classifier using convolutional neural network / |
| Statement of responsibility, etc. |
Justine Carlo De Vega, Cherry Laurino, and Aidhel Olaes. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Rosario, Cavite : |
| Name of publisher, distributor, etc. |
Cavite State University-CCAT Campus, |
| Date of publication, distribution, etc. |
2019. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xiv, 56 leaves : |
| Other physical details |
illustrations ; |
| Dimensions |
28 cm |
| 500 ## - GENERAL NOTE |
|---|
| General note |
An Undergraduate Thesis (BSCS) -- Cavite State University-CCAT Campus, 2019. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and appendices. |
| 520 ## - SUMMARY, ETC. |
|---|
| Thesis Abstract |
<a href="DE VEGA, JUSTINE CARLO D. LAURINO, CHERRY J. AND OLAES, AIDHEL D.A ROOT CROPS CLASSIFIER USING CONVOLUTIONAL NEURAL NETWORK. Undergraduate Thesis. Bachelor of Science in Computer Science. Cavite State University-CCAT Campus, Rosario, Cavite. June 2019. Adviser: Ms. Yvana Jardine Nocon.<br/><br/>The study, a root crops classification system using convolutional neural network, was conducted from August 2017 to March 2019. Specifically, the study aimed to: 1) obtain necessary requirements needed in classifying root crops, including its dataset, characteristics and information; 2) analyze the acquired requirements and identify the appropriate algorithm to be used; 3) design and develop the application that can run in a mobile platform, using an appropriate mobile application development tools; 4) test the accuracy and compatibility of the application; and 5) assess the application using modified evaluation instrument adapted from ISO-IEC 25010.<br/><br/>The developers used the rapid application development system to accomplish the root crops classification system. In this model, the analysis, design and implementation stage interacts continuously to create the prototype for testing and evaluation.<br/><br/>The system was evaluated by five respondents composed of IT experts of Cavite State University-CCAT. The root crops classifier gained a total score of 4.25/5, suggesting a very satisfactory performance. The application is able to meet its purpose of using image processing to detect and identify root crops available in the market.">DE VEGA, JUSTINE CARLO D. LAURINO, CHERRY J. AND OLAES, AIDHEL D.A ROOT CROPS CLASSIFIER USING CONVOLUTIONAL NEURAL NETWORK. Undergraduate Thesis. Bachelor of Science in Computer Science. Cavite State University-CCAT Campus, Rosario, Cavite. June 2019. Adviser: Ms. Yvana Jardine Nocon.<br/><br/>The study, a root crops classification system using convolutional neural network, was conducted from August 2017 to March 2019. Specifically, the study aimed to: 1) obtain necessary requirements needed in classifying root crops, including its dataset, characteristics and information; 2) analyze the acquired requirements and identify the appropriate algorithm to be used; 3) design and develop the application that can run in a mobile platform, using an appropriate mobile application development tools; 4) test the accuracy and compatibility of the application; and 5) assess the application using modified evaluation instrument adapted from ISO-IEC 25010.<br/><br/>The developers used the rapid application development system to accomplish the root crops classification system. In this model, the analysis, design and implementation stage interacts continuously to create the prototype for testing and evaluation.<br/><br/>The system was evaluated by five respondents composed of IT experts of Cavite State University-CCAT. The root crops classifier gained a total score of 4.25/5, suggesting a very satisfactory performance. The application is able to meet its purpose of using image processing to detect and identify root crops available in the market.</a> |
| 546 ## - LANGUAGE NOTE |
|---|
| Language note |
In English text. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Convolutional neural network. |
| 9 (RLIN) |
11823 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Root crops. |
| 9 (RLIN) |
11927 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Classification. |
| 9 (RLIN) |
11928 |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Image processing. |
| 9 (RLIN) |
5797 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Laurino, Cherry, author. |
| 9 (RLIN) |
11929 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Olaes, Aidhel, author. |
| 9 (RLIN) |
11930 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nocon, Yvana Jardine R., adviser. |
| 9 (RLIN) |
11767 |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Nabalit, Karlo Jose E., technical critic. |
| 9 (RLIN) |
11931 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Koha item type |
Thesis/Manuscripts/Dissertations |
| Classification part |
QA 76.87 D48 2019 |
| Call number prefix |
UM |
