In this work, we present a framework for product quality inspection based on deep learning techniques. First, we categorize several deep learning models that can be applied to product inspection systems. Also we explain entire steps for building a deep learning-based inspection system in great detail. Second, we address connection schemes that efficiently link the deep learning models to the product inspection systems. Finally, we propose an effective method that can maintain and enhance the deep learning models of the product inspection system. It has good system maintenance and stability due to the proposed methods. All the proposed methods are integrated in a unified framework and we provide detailed explanations of each proposed method. In order to verify the effectiveness of the proposed system, we compared and analyzed the performance of methods in various test scenarios.
翻译:在这项工作中,我们提出了一个基于深层学习技术的产品质量检查框架。首先,我们将若干可适用于产品检查系统的深层学习模式分类。我们还要详细解释建立深层学习检查系统的整个步骤。第二,我们处理将深层学习模式与产品检查系统有效地联系起来的连接计划。最后,我们提出一个能够维持和加强产品检查系统深层学习模式的有效方法。由于建议的方法,它具有良好的系统维护和稳定性。所有拟议方法都被纳入一个统一的框架,我们对每一种拟议方法作出详细解释。为了核实拟议系统的有效性,我们比较并分析了各种测试情景中方法的绩效。