The text segmentation by neural networks of image segmentation.

Abstract

The article highlights the importance of text segmentation in the field of natural language processing (NLP), especially in light of the development of large language models such as GPT-4. It discusses the use of specialized segmentation neural networks for various tasks, such as processing passport data and other documents, and points out the possibility of integrating these technologies into mobile applications. The use of neural network architectures, geared towards image processing, for text segmentation is considered. The study describes the application of networks such as PSPNet, U-Net, and U-Net++ for processing textual data, with an emphasis on adapting these networks to text tasks and evaluating their effectiveness. The potential of the multimodal capabilities of modern neural networks and the need for further research in this field are emphasized.