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DC Field | Value | Language |
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dc.contributor.author | Raslapat Suteeca | en_US |
dc.contributor.author | Pasit Chalernkhawn | en_US |
dc.contributor.author | Khawsroung Pakdee | en_US |
dc.date.accessioned | 2020-04-02T14:58:47Z | - |
dc.date.available | 2020-04-02T14:58:47Z | - |
dc.date.issued | 2019-12-01 | en_US |
dc.identifier.other | 2-s2.0-85082394602 | en_US |
dc.identifier.other | 10.1109/TIMES-iCON47539.2019.9024510 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85082394602&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/67646 | - |
dc.description.abstract | © 2019 IEEE. The purpose of this research aims the development of a succulent image searching system. Based on deep learning technique provides information about succulent such as name, scientific name, family, characteristic, nursery, and breed by image searching and measuring the accuracy of models for predicting data in this development using web application to facilities for succulent image searching system. The Development of a succulent image searching system Based on deep learning technique and using Convolutional Neural Network (CNN) to create a model for a succulent image prediction. With adapted waterfall model of the software development Life Cycle (SDLC) to develop a succulent image searching system that has the efficacy of data and image prediction. The results from the independent study are predicting the succulent image searching system with more than 75% accuracy and meet the requirements of the system in all respects. | en_US |
dc.subject | Business, Management and Accounting | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | Development of Succulent Species Prediction System by Deep Learning Technique | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | TIMES-iCON 2019 - 2019 4th Technology Innovation Management and Engineering Science International Conference | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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