DREAM GENERATION USING AI: COMPARISON OF ALGORITHMS

Author(s)	JWALA JOSE, DR. B. SURESH KUMAR, PRASEETHA N A
Country	India
Abstract	Dream generation is an emerging field within artificial intelligence that aims to replicate the human experience of dreaming through computational models. This paper compares various AI algorithms used for dream generation, evaluating their performance, creativity, and computational efficiency. We explore Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer-based models, providing a comprehensive analysis of their strengths and weaknesses. Our results indicate that each model has unique advantages, suggesting potential hybrid approaches for future research.
Keywords	Dream Generation, AI, GAN, VAEs, Transformers, Creativity, Coherence, Computational Efficiency, FID, IS, EEG signal.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-07
Cite This	DREAM GENERATION USING AI: COMPARISON OF ALGORITHMS - JWALA JOSE, DR. B. SURESH KUMAR, PRASEETHA N A - IJFMR Volume 6, Issue 6, November-December 2024. DOI 10.36948/ijfmr.2024.v06i06.32281
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.32281
Short DOI	https://doi.org/g8t3kg

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