Recognizing and Grading 3D Modeling Objects Using YOLO Based Deep Learning Network
Huihui Chen, Chiao-Wen Kao, Bor‐Jiunn Hwang, Kuo‐Chin Fan · 2019
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.