Recognizing and Grading 3D Modeling Objects Using YOLO Based Deep Learning Network

Hui Hui Chen, Chiao Wen Kao, Bor Jiunn Hwang, Kuo Chin Fan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

This study proposes a novel approach using YOLO based deep learning network to help the teacher grading 3D modeling objects created by the learners automatically. The training dataset is the collections of rendering outputs from the teacher's 3D modeling object. The testing data is the rendering outputs of the learners' projects. The grading will rely on the testing results of recognition confidences. This is an initial study from draft inspiration by the deep learning network on object detections and recognitions. More applications and modifications are to be discussed, designed and examined in further studies.

原文???core.languages.en_GB???
主出版物標題Proceedings of 2019 International Conference on Machine Learning and Cybernetics, ICMLC 2019
發行者IEEE Computer Society
ISBN(電子)9781728128160
DOIs
出版狀態已出版 - 7月 2019
事件18th International Conference on Machine Learning and Cybernetics, ICMLC 2019 - Kobe, Japan
持續時間: 7 7月 201910 7月 2019

出版系列

名字Proceedings - International Conference on Machine Learning and Cybernetics
2019-July
ISSN(列印)2160-133X
ISSN(電子)2160-1348

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???18th International Conference on Machine Learning and Cybernetics, ICMLC 2019
國家/地區Japan
城市Kobe
期間7/07/1910/07/19

指紋

深入研究「Recognizing and Grading 3D Modeling Objects Using YOLO Based Deep Learning Network」主題。共同形成了獨特的指紋。

引用此