Dataset anonymization and road signs detection

Micro mobility vehicles and renting services have seen an unprecedented spike due to the growth of the population in urban areas. Simultaneously, automotive technology for autonomous driving has drastically improved and entered the global market. In this thesis we propose the testbed for a future assisted driving application. This prototype is based on an object detector using a Region-Based Convolutional Neural Network trained to detect traffic road signs specific to micro-mobility vehicles. In order to train this model, it’s necessary to use a dataset that contains confidential data of many citizens, we also introduce a solution to manage this sensitive data under the General Data Protection Regulation using pre-trained models for face and number plate detection