This paper describes an approach for identifying and appending interior design style information stochastically with reference images and a deep-learning model. In the field of interior design, design style is a useful concept and has played an important role in helping people understand and communicate interior design. Previous studies have focused on how the interior design style categories can be defined. On the other hand, this paper focuses on how stochastically recognizing the design style of given interior design reference images using a deep learning-based data-driven approach. The proposed method can be summarized as follows: (1) data preparation based on a general design style definition, (2) implementing an interior design style recognition model using a pre-trained VGG16 model, (3) training and evaluating the trained model, and (4) demonstration of stochastic detection of interior design styles for reference images. The result shows that the trained model automatically recognizes the design styles of given interior images with probability values. The recognition results, model, and trained image set contribute to facilitating the management and utilization of an interior design references database.

中文翻译：

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使用参考模型的深度学习模型对室内设计风格进行随机检测

本文介绍了一种用于随机识别和附加参考图像和深度学习模型的室内设计风格信息的方法。在室内设计领域，设计风格是一个有用的概念，并且在帮助人们理解和传达室内设计方面发挥了重要作用。先前的研究集中于如何定义室内设计风格类别。另一方面，本文重点介绍如何使用基于深度学习的数据驱动方法随机地识别给定的室内设计参考图像的设计风格。提出的方法可以概括如下：（1）基于一般设计风格定义的数据准备；（2）使用预训练的VGG16模型实现室内设计风格识别模型；（3）训练和评估训练后的模型；（4）随机检测参考图像的室内设计风格。结果表明，训练后的模型会自动识别具有概率值的给定内部图像的设计样式。识别结果，模型和训练有素的图像集有助于简化室内设计参考数据库的管理和利用。