论文标题
重用人工神经网络的文物的存储库
Repository for Reusing Artifacts of Artificial Neural Networks
论文作者
论文摘要
人工神经网络（ANN）取代了各种域中的常规软件系统，例如机器翻译，自然语言处理和图像处理。那么，为什么我们需要一个用于人工神经网络的存储库？这些系统是用标记的数据开发的，我们在用于培训和测试网络的数据之间具有很强的依赖性。另一个挑战是数据质量以及重复使用。在那里，我们试图应用不限于模型的经典软件工程的概念，而数据和代码在其他项目中都没有处理。想到的第一个问题可能是，为什么我们不使用Github（作为我们的问题广泛传播的工具Github）。而Github的原因虽然在同类产品中非常好，但不是为了机器学习设备而开发的，而是专注于软件重复使用的原因。除此之外，GitHub不允许直接在平台上执行代码，这对于一个项目的协作工作将非常方便。
Artificial Neural Networks (ANNs) replaced conventional software systems in various domains such as machine translation, natural language processing, and image processing. So, why do we need an repository for artificial neural networks? Those systems are developed with labeled data and we have strong dependencies between the data that is used for training and testing our network. Another challenge is the data quality as well as reuse-ability. There we are trying to apply concepts from classic software engineering that is not limited to the model, while data and code haven't been dealt with mostly in other projects. The first question that comes to mind might be, why don't we use GitHub, a well known widely spread tool for reuse, for our issue. And the reason why is that GitHub, although very good in its class is not developed for machine learning appliances and focuses more on software reuse. In addition to that GitHub does not allow to execute the code directly on the platform which would be very convenient for collaborative work on one project.
