A New Innovative Research Model on the Interestingness Expression of TechnoArt
Keywords:
TechnoArt, Virtual Reality, Generative Adversarial Network (GANs), Fuzzy Logic, Emotional IntelligenceAbstract
Virtual Reality (VR) is an advanced technology that immerses users in a simulated environment, providing a multisensory experience that can replicate real-world scenarios or create entirely fictional worlds. Despite its potential, VR technology has challenges to overcome, such as motion sickness for some users, the need for powerful hardware to render realistic graphics, and the high cost of quality VR systems. The paper introduces a pioneering exploration into the realm of virtual reality-based TechnoArt creation by harnessing the potential of Generative Adversarial Networks (GANs). Through seamlessly integrating GANs, virtual reality, and artistic creativity, a groundbreaking framework emerges, enabling the generation of immersive and innovative artworks. The study establishes a comprehensive methodology that amalgamates fuzzy logic for quality assessment, emotional analysis, and classification techniques to comprehensively evaluate the produced artworks across various dimensions. The simulation results vividly exemplify the capabilities of this approach, yielding a diverse array of TechnoArt pieces with distinctive levels of quality, emotional resonance, and originality. The comparison with alternative classification methods, including Artificial Neural Networks (ANN) and Recurrent Neural Networks (RNN), underscores the effectiveness of the proposed technique in terms of accuracy, precision, recall, and F1-Score. The outcomes not only enrich the landscape of digital art but also provide invaluable insights into the convergence of advanced technologies like GANs and virtual reality with artistic expression.
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