标题： 基于VGG19的动态神经风格迁移用于艺术图像生成 显示英文标题

标题： Dynamic Neural Style Transfer for Artistic Image Generation using VGG19

摘要： throughout history, humans have created remarkable works of art, but artificial intelligence has only recently started to make strides in generating visually compelling art. 过去的几个年中，突破集中在使用卷积神经网络（CNN）来分离和操作图像的内容和风格，应用纹理合成技术。 然而，一些当前的技术仍然遇到障碍，包括处理时间长、风格图像选择有限以及无法修改风格权重比例。 我们提出了一种神经风格迁移系统，可以将各种艺术风格添加到所需图像上，以解决这些限制，允许灵活调整风格权重比例并减少处理时间。 该系统使用VGG19模型进行特征提取，确保高质量、灵活的风格化而不损害内容完整性。 显示英文摘要

摘要： Throughout history, humans have created remarkable works of art, but artificial intelligence has only recently started to make strides in generating visually compelling art. Breakthroughs in the past few years have focused on using convolutional neural networks (CNNs) to separate and manipulate the content and style of images, applying texture synthesis techniques. Nevertheless, a number of current techniques continue to encounter obstacles, including lengthy processing times, restricted choices of style images, and the inability to modify the weight ratio of styles. We proposed a neural style transfer system that can add various artistic styles to a desired image to address these constraints allowing flexible adjustments to style weight ratios and reducing processing time. The system uses the VGG19 model for feature extraction, ensuring high-quality, flexible stylization without compromising content integrity.