开放神经图像生成器

Andrei-Marius Avram, Luciana Morogan, Stefan-Adrian Toma
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引用次数: 0

摘要

生成模型是一种统计模型,它使用无监督学习从样本中学习真实的底层数据分布,旨在生成具有一些变化的新数据点。在本文中,我们介绍了OpenNIG(开放神经图像生成器),一个用于图像生成的开源神经网络工具包。它提供了轻松训练、验证和测试先进模型状态的可能性。该框架还包含一个模块,使用户可以直接下载和处理深度学习中使用的一些最常见的数据库。OpenNIG可以通过GitHub免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
OpenNIG - Open Neural Image Generator
Generative models are statistical models that learn a true underlying data distribution from samples using unsupervised learning, aiming to generate new data points with some variation. In this paper, we introduce OpenNIG (Open Neural Image Generator), an open-source neural networks toolkit for image generation. It offers the possibility to easily train, validate and test state of the art models. The framework also contains a module that enables the user to directly download and process some of the most common databases used in deep learning. OpenNIG is freely available via GitHub.
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