Аннотации:
This article examines the applicability of neural networks, particularly the DCGAN architecture, to logos generation. The model was trained on a dataset consisting of 22000 logo images giving a good result for the hardware capabilities provided for free by Google Colab. Essentially by increasing the training time and increasing the complexity of the model can achieve very good results.