摘要
由新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-关于机器人的详细数据已经呈现。根据NewsRx编辑在匈牙利德布雷森的新闻报道，Research称：“工业4.0已经成为当今工业科学中最主要的研究领域之一。许多工业机械装置没有允许在调试中使用图像分析技术的现代标准DS。”这项研究的资助者包括匈牙利国家研究、发展和创新基金。新闻编辑们引用了德布雷森大学的一篇研究文章：“智能材料处理、分拣和物体识别是不可能的，我们为现有的机器人设备提出了一种新的深度学习方法，该方法可以在不经过改进的情况下应用于未来的机器人。在实现中，为植入机设计了需要重新认识的PCB继电器模块的三维CAD模型,并利用FDM三维打印技术开发制造了铝型材装配零件。我们还应用基于三维CAD模型的深度学习算法，通过CGI渲染生成一个对象数据集，用图像到图像的转换技术训练深度学习算法。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Data detailed on robotics have been presented. Ac cording to news reporting out of Debrecen, Hungary, by NewsRx editors, research stated, "Industry 4.0 has become one of the most dominant research areas in indu strial science today. Many industrial machinery units do not have modern standar ds that allow for the use of image analysis techniques in their commissioning." Funders for this research include National Research, Development, And Innovation Fund of Hungary. The news editors obtained a quote from the research from University of Debrecen: "Intelligent material handling, sorting, and object recognition are not possibl e with the machinery we have. We therefore propose a novel deep learning approac h for existing robotic devices that can be applied to future robots without modi fication. In the implementation, 3D CAD models of the PCB relay modules to be re cognized are also designed for the implantation machine. Alternatively, we devel oped and manufactured parts for the assembly of aluminum profiles using FDM 3D p rinting technology, specifically for sorting purposes. We also apply deep learni ng algorithms based on the 3D CAD models to generate a dataset of objects for ca tegorization using CGI rendering. We generate two datasets and apply image-to-im age translation techniques to train deep learning algorithms."
NETL
NSTL