论文标题
在工程图中自动检测和分类
Automatic Detection and Classification of Symbols in Engineering Drawings
论文作者
论文摘要
提出了一种在设计图，绘图或计划布局中查找和分类各种组件和对象的方法。该方法会自动找到传奇表中存在的对象，并借助多个深神经网络找到其位置，计数和相关信息。该方法已在多个图纸或设计模板上进行了预训练，以学习可能有助于表示新模板的功能集。对于以前看不见的模板，它不需要使用模板数据集进行任何培训。所提出的方法可能在多个行业应用程序中很有用，例如设计验证，对象计数，组件的连接等。该方法是通用的，域是独立的。
A method of finding and classifying various components and objects in a design diagram, drawing, or planning layout is proposed. The method automatically finds the objects present in a legend table and finds their position, count and related information with the help of multiple deep neural networks. The method is pre-trained on several drawings or design templates to learn the feature set that may help in representing the new templates. For a template not seen before, it does not require any training with template dataset. The proposed method may be useful in multiple industry applications such as design validation, object count, connectivity of components, etc. The method is generic and domain independent.
