论文标题
图像到图像神经网络，用于添加和减去一对不是很大的神经网络
Image-to-image Neural Network for Addition and Subtraction of a Pair of Not Very Large Numbers
论文作者
论文摘要
回顾计算器的历史，可以看到它们的功能降低，并且随着时间的流逝而变得更加昂贵。现代计算器在个人计算机上运行，并以60 fps的形式绘制，只是为了帮助我们使用鼠标指针单击几位数字。搜索引擎通常被用作计算器，这意味着如今我们需要互联网只是添加两个数字。在本文中，我们建议进一步训练卷积神经网络，该网络拍摄简单数学表达的图像并生成答案的图像。该神经计算器仅适用于成对的两位数数字，仅支持加法和减法。另外，有时会犯错误。我们保证，拟议的计算器是人类的一小步，但对人类来说是一个巨大的飞跃。
Looking back at the history of calculators, one can see that they become less functional and more computationally expensive over time. A modern calculator runs on a personal computer and is drawn at 60 fps only to help us click a few digits with a mouse pointer. A search engine is often used as a calculator, which means that nowadays we need the Internet just to add two numbers. In this paper, we propose to go further and train a convolutional neural network that takes an image of a simple mathematical expression and generates an image of an answer. This neural calculator works only with pairs of double-digit numbers and supports only addition and subtraction. Also, sometimes it makes mistakes. We promise that the proposed calculator is a small step for man, but one giant leap for mankind.
