(2024-03-19) Silva, Romão Charles Silva e; Santos, Alyson de Jesus dos Santos; http://lattes.cnpq.br/5998752909180697; Santos, Alyson de Jesus dos; http://lattes.cnpq.br/5998752909180697; Martins, Gilbert Breves; http://lattes.cnpq.br/4932200790121123; Rodrigues, Marlos André Silva; http://lattes.cnpq.br/0682962508867807
This work aims to develop a system based on machine learning that differentiates images
of people generated by artificial intelligence from real people, a capability that can be very
useful for identifying scams that use generated images. The development of the project
was done in 3 main steps: data organization, training and testing. The system was entirely
made in Google Colab, therefore, it used Python and the main development tool
Tensorflow, two models were trained, one of which has almost twice as many images
used for training, with the intention of observing the consequences of using a larger set.
At the end of the project, the quantitative and qualitative results of the image classification
are shown.
