利用图像分割神经网络进行文本分割。

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Pub Date : 2024-03-20 DOI:10.15407/jai2024.01.046
Slyusar V
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引用次数: 0

摘要

文章强调了文本分割在自然语言处理(NLP)领域的重要性,尤其是在开发出 GPT-4 等大型语言模型的情况下。文章讨论了在处理护照数据和其他文件等各种任务中使用专业分割神经网络的情况,并指出了将这些技术集成到移动应用中的可能性。研究还考虑了在文本分割中使用面向图像处理的神经网络架构。该研究介绍了 PSPNet、U-Net 和 U-Net++ 等网络在处理文本数据方面的应用,重点是将这些网络适用于文本任务并评估其有效性。研究强调了现代神经网络多模态功能的潜力以及在该领域开展进一步研究的必要性。
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The text segmentation by neural networks of image segmentation.
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.
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来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
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