Predicting a vehicle or pedestrian's next move with neural networks

Autor:	Ronald Hugh Miller, Anya Lynn Tascillo, David M. DiMeo, Perry Robinson MacNeille
Rok vydání:	2003
Předmět:	ComputingMethodologies_PATTERNRECOGNITION Recurrent neural network Contextual image classification Artificial neural network business.industry Computer science Time delay neural network Motion estimation Computer vision Recurrent neural nets Artificial intelligence Pedestrian business
Zdroj:	Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
Popis:	For a given digitized view of a driving scenario, motion clusters are formed, indicating possible moving object threats to the driver. Recurrent neural networks minimize hopping between clusters and predict a cluster's next location. Frequency analysis then categorizes as significant motion, and then as either head-on/away or transverse motion.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9f9bb4e895c2d608c9669b17fbc649a4 https://doi.org/10.1109/ijcnn.2002.1007502 Zobrazit plný text záznamu