@inproceedings{821895a77c914ed2a43e4ba404f1cadc,
title = "Real Time Object Detection Based on Deep Neural Network",
abstract = "In this research we focus on using deep learning for the training of real time detection of defected Nails and Nuts on a high speed production line using You Only Look Once (YOLO) algorithm for real time object detection and trying to increase the precision of detection and decrease the problems facing real time object detection models like Object occlusion, different orientation for objects, lighting conditions, undetermined moving objects and noise. A series of experiments have been done to achieve high prediction accuracy, the experimental results made on our costumed pascal visual object classes (VOC) dataset demonstrated that the mean Average Precision (mAP) could reach 85\%. The proposed model showed very good prediction accuracy on the test dataset.",
keywords = "Computer vision, Convolutional Neural Network, Deep learning, Object detection, Visual servoing, YOLOv2",
author = "Tarek Teama and Hongbin Ma and Ali Maher and Kassab, \{Mohamed A.\}",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
year = "2019",
doi = "10.1007/978-3-030-27538-9\_42",
language = "English",
isbn = "9783030275372",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "493--504",
editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Yuwang Liu and Zhaojie Ju and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings",
address = "Germany",
}