Detecting Turistic Places with Convolutional Neural Networks

A mobile application was developed for the recognition of places from a photo using the technique “content based photo geolocation as spatial database queries”. For this purpose, an investigation and analysis of the different existing methods that allow us to recognize images from a photo was carried out in order to select the best possible model and then improve it. Performance comparisons, comparison of number of parameters, Error: imagenet and the Brain-Score were made; once the best model was obtained, the algorithm was implemented and with the results the expected information of the place in the photo was shown. The purpose of this information is to recommend nearby places of interest. In the development stage, first, we implement an architecture with convolutional neural networks VGG16, for the recognition of places, the model was trained, after obtaining a trained model with successful results, the construction phase of the application continued. mobile in order to test the operation of the model. Users will use the app by submitting a photo which will query the trained model, and results will be obtained in seconds, information that will provide a better experience when visiting unknown places.