Portfolio Category: Saturday program

Lecture

Recent technological advances have made it possible to digitize an increasing number of works of art. It is no wonder, then, that the automatic classification, indexing and retrieval of fine art images has received increased attention in recent years. However, compared to the classification of natural objects, the classification of works of art is a much more challenging task. Convolutional neural networks (CNN), which consist of a number of layers of convolutional matrix operations, are an ideal solution for image analysis and object identification. CNN uses a similar concept to the graphics filters used in graphics editors, but in a much more complex and computationally intensive manner.

Workshop and lecture

Algorithmic art seldom creates finished and unchanging works. Generative creation is usually based on gradual or even never-ending development. During the generation, aesthetic solutions are tentatively sought for which we do not know the specific procedure or exact parameters. Algorithmic images are developed on the basis of interaction with the creator or with the use of chance (and more and more recently with the contribution of artificial intelligence). The lecture with practical examples presents various types of creative applications for rendering time and randomness in computer graphics. You will be convinced that if you manage to capture chance at the right time, it can bring you an unprecedented aesthetic experience.

lecture