Abstract
Every year rendering logos becomes an increasingly important task in various fields. One of the most interesting methods for rendering logos is the use of neural networks. This paper proposes a method for rendering logos using a convolutional neural network (CNN), specially trained to classify objects based on a single keyword and to select parametric characteristics of the logo. Special attention is paid to the ergonomic evaluation of resulting logos and the feasibility of the proposed method is experimentally confirmed. The research has shown that the results obtained are superior compared to the most modern approaches.
Highlights
Logos, known as trademarks, are important in today's marketing world
The most discussed logos are aesthetically appealing, distinctive, memorable, scalable, easy to use, adaptable, and they effectively convey the characteristics of the organization
During rendering the network generates ratings for each logo element in each box and makes adjustments for the box according to the specified parameters to design and visualize the shape of the object better
Summary
Known as trademarks, are important in today's marketing world. Logo rendering is a key issue in a wide range of areas. The most discussed logos are aesthetically appealing, distinctive, memorable, scalable, easy to use, adaptable (in color and black and white), and they effectively convey the characteristics of the organization. Based on the mentioned above, it can be argued that creating an effective visual representation of the brand requires much more than just graphic design. For this reason, the paper emphasizes the rules that were laid down in the basis of functioning the developed system [1]. One can achieve balance by maintaining the" weight " of graphics, color, size, and symmetry. When using colors in the logo design, one should maintain a constant color palette. Using simple forms makes it as easy as possible to perceive and remember the logo
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