Deep learning using computer vision in self driving cars for lane and traffic sign detection

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-10-05T16:33:26Z
Fecha de publicación2021-01-01
ResumenRecently, the amount of research in the field of self-driving cars has grown significantly with autonomous vehicles having clocked in more than 10 million miles, providing a substantial amount of data for use in training and testing. The most complex part of training is the use of computer vision for feature extraction and object detection in real-time. Much relevant research has been done on improving the algorithms in the area of image segmentation. The proposed idea presents the use of Convoluted Neural Networks using Spatial Transformer Networks and lane detection in real time to increase the efficiency of autonomous vehicles. The depth of the neural network will help in training vehicles and during the testing phase, the vehicles will learn to make decisions based on the training data. In case of sudden changes to the environment, the vehicle will be able to make decisions quickly to prevent damage or danger to lives. Along with lane detection, a self-driving car must also be able to detect traffic signs. The proposed approach uses the Adam Optimizer which runs on top of the LeNet-5 architecture. The LeNet-5 architecture is analyzed and compared with the Feed Forward Neural Network approach. The accuracy of the LeNet-5 architecture was found to be 97\% while the accuracy of the Feed Forward Neural Network was 94\%.es_ES
Doihttps://doi.org/10.1007/s13198-021-01127-6es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/5277
Idiomaenes_ES
EditorialSPRINGER INDIAes_ES
RelaciónInternational Journal of System Assurance Engineering and Managementes_ES
URL relacionadohttps://doi.org/10.1007/s13198-021-01127-6es_ES
DerechosAcceso restringido / Suscripción (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_16eces_ES
FuenteInternational Journal of System Assurance Engineering and Management
Palabra claveComputer visiones_ES
Palabra claveDeep learninges_ES
Palabra claveSelf-driving carses_ES
Palabra claveAutonomous vehicleses_ES
TítuloDeep learning using computer vision in self driving cars for lane and traffic sign detectiones_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorKanagaraj, Nitin
AutorHicks, David
AutorGoyal, Ayush
AutorTiwari, Sanju
AutorSingh, Ghanapriya
AutorKanagaraj, Nitines_ES
AutorHicks, Davides_ES
AutorGoyal, Ayushes_ES
AutorTiwari, Sanjues_ES
AutorSingh, Ghanapriyaes_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número6es_ES
Rango de páginas1011-1025es_ES
URL relacionadahttps://doi.org/10.1007/s13198-021-01127-6
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen12es_ES

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