Abstract and keywords
Abstract (English):
The paper discusses approaches to modeling the process of trademark creation using artificial neural networks. An analysis of modern generative architectures used in visual design, including diffusion models and generative adversarial networks (GANs), is presented. A conceptual model of an automated trademark design system is proposed, including the stages of training, generation, and originality assessment of images. The criteria for evaluating the aesthetic quality and uniqueness of generated signs are considered. The obtained results can be applied to optimize creative processes in branding and corporate identity development.

Keywords:
artificial intelligence, neural networks, generative design, modeling, trademark, computer vision, machine learning
References

1. Goodfellow I., Pouget‑Abadie J., Mirza M., Xu B., Warde‑Farley D., Ozair S., Courville A., Bengio Y. Generative Adversarial Nets // Advances in Neural Information Processing Systems (NeurIPS), 2014. – S. 41-42

2. Karras T., Laine S., Aittala M., Hellsten J., Lehtinen J., Aila T. Analyzing and Improving the Image Quality of StyleGAN // arXiv preprint arXiv:1912.04958, 2019.

3. Rombach R., Blattmann A., Lorenz D., Esser P., Ommer B. High‑Resolution Image Synthesis with Latent Diffusion Models // Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. — S. 2-6 DOI: https://doi.org/10.1109/CVPR52688.2022.01042

4. Radford A., Kim J. W., Hallacy C., Ramesh A., Goh G., Agarwal S., et al. Learning Transferable Visual Models from Natural Language Supervision // Proceedings of the 38th International Conference on Machine Learning (ICML), 2021. — S. 7-11

5. Skillbox. Top‑10 servisov dlya sozdaniya logotipov s pomosch'yu iskusstvennogo intellekta. – URL: https://skillbox.ru/media/design/10-ai-for-logos/ (data obrascheniya: 09.10.2025).

Login or Create
* Forgot password?