Evaluation of Deep Learning YOLOv3 Algorithm for Object Detection and Classification | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 7, Volume 30, Issue 1, January 2021, Page 52-57 PDF (1 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2021.146237 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Weal A. Ezat; Mohamed M. Dessouky1; Nabil A. Ismail2 | ||||
| 1Dept. of Computer Science and Engineering, Faculty of Electronic Engineering Menoufia University. | ||||
| 2Dept. of Computer Science and Engineering, Faculty of Electronic EngineeringMenoufia University email | ||||
| Abstract | ||||
| You Only Look Once version 3 (YOLOv3) is a deep learning model for object detection and classification. It is a single neural network architecture model that uses features from the feeding images and predicts bounding box for all classes of image simultaneously. This paper descript an experimental work for train the deep learning model based on YOLOv3 architecture implemented using Tensor Flow as a deep learning framework. The training process had been done using the data-set PASCAL VOC 2007 and data-set PASCAL VOC 2012 and using The Adaptive Moment Estimation Optimizer (ADM optimizer). The trained model is then tested by using the VOC 2007 test data-set. The final results evaluate the YOLOv3 deep learning model performance for object detection and classification. | ||||
| Keywords | ||||
| Deep learning; YOLOv3; Object detection | ||||
| References | ||||
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