THE PICTURE WORLD OF THE FUTURE: AI TEXT-TO-IMAGE AS A NEW ERA OF VISUAL CONTENT CREATION
Keywords:
AI text-to-image, deep learning, generative adversarial networks, GANs, computer visionAbstract
In this paper, we investigated the technology of AI text-to-image and its various applications in different industries. We reviewed literature on various methods of AI Text in Image, compared their advantages and limitations, and discussed potential use cases in different fields such as design, medicine, architecture, and art. One important factor that affects the performance of AI text-to-image is the size of the training dataset. To achieve high accuracy and quality in generating images, it is necessary to use large datasets that are diverse and of high quality. It is also important that the datasets consist of descriptive texts that describe the different characteristics of the generated images. To improve the accuracy and quality of generating images, new datasets and techniques are being developed to create diverse and high-quality texts.
We also described the methodology we used in the research, presented results, analyzed challenges, and discussed ethical considerations arising from the use of this technology. Finally, we highlighted that AI text-to-image represents an important and innovative technology with great potential for transforming various fields, while considering ethical guidelines for the use of this technology.
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