| dc.description.abstract | With the development of modern technology today, its application to various
fields is extremely important. Especially in the field of traffic safety, with a
society where the occurrence of traffic accidents is very high, in which traffic sign
recognition is one of the essential topics for everyone. Therefore, in this thesis,
the goal is to provide a model that can identify and classify types of traffic signs
in Vietnam in the most accurate way. And to complete this project, it is necessary
to rely on Deep Convolutional Neural Network (CNN) and Resnet-50 model to
identify and provide parameters for classification of traffic signs. Along with
using data augmentation techniques to create image complexity and with
convolution layers combining modern methods such as batch normalization, the
initialization to improve the accuracy of the problem. | en_US |
