@inproceedings{01463a029c6940a9a71949bcb97ea999,
title = "An improved BP neural network based on GA for 3D laser data repairing",
abstract = "Affected by scanning object, environment, scanning speed and user's operation .etc, some information of the object's surface can't be detected by the laser scanner. Aiming at the data loss in laser detecting , the paper presents an improved BP neural network based on GA for 3D laser data repairing, the novelty of this method is adopting Genetic Algorithm(GA) to optimize the configure and weight of network, and at the same time combining Back Propagation(BP) Algorithm to find optimal approximation. The simulation shows the improved BP neural network based on GA has a faster constringency speed and better repairing precision than traditional BP neural network and GA algorithm. Lastly, the paper gives the result of repairing the point cloud collected by 3D information reconstruction system using this network.",
keywords = "Bp network, Data repairing, GA, Laser scanner",
author = "Shouqian Yu and Lixia Rong and Weihai Chen and Xingming Wu",
year = "2008",
doi = "10.1109/RAMECH.2008.4690878",
language = "英语",
isbn = "9781424416769",
series = "2008 IEEE International Conference on Robotics, Automation and Mechatronics, RAM 2008",
pages = "571--576",
booktitle = "2008 IEEE International Conference on Robotics, Automation and Mechatronics, RAM 2008",
note = "2008 IEEE International Conference on Robotics, Automation and Mechatronics, RAM 2008 ; Conference date: 21-09-2008 Through 24-09-2008",
}