论文标题
兔子，蟾蜍和月球：机器可以将它们分为一个类吗？
Rabbit, toad, and the Moon: Can machine categorize them into one class?
论文作者
论文摘要
最近的机器学习算法（例如神经网络）可以以很高的精度在视频帧中对对象和动作进行分类。在这里，我讨论了基于基础动态模式的对象的分类，这些模式引用了一种传统，即兔子，蟾蜍和月球之间的联系，这可以在几种文化中看到。为了将它们分为一个类，一种基本的行为模式（环状外观和消失）作为特征点。诸如行为的形状和时间尺度之类的静态特征对于此分类不是必不可少的。在认知语义中，引入了图像模式来描述事件的基础模式。如果获得了这些图像模式，则一台机器可能能够将兔子，蟾蜍和月球归类为同一类。对于学习，显示边界框或细分的视频帧可能会有所帮助。尽管此讨论是初步的，并且许多任务仍有待解决，但基于基础行为的分类可能是认知过程和计算机科学的重要主题。
Recent machine learning algorithms such as neural networks can classify objects and actions in video frames with high accuracy. Here, I discuss a classification of objects based on basal dynamic patterns referencing one tradition, the link between rabbit, toad, and the Moon, which can be seen in several cultures. In order for them to be classified into one class, a basic pattern of behavior (cyclic appearance and disappearance) works as a feature point. A static character such as the shape and time scale of the behavior are not essential for this classification. In cognitive semantics, image schemas are introduced to describe basal patterns of events. If learning of these image schemas is attained, a machine may be able to categorize rabbit, toad, and the Moon as the same class. For learning, video frames that show boundary boxes or segmentation may be helpful. Although this discussion is preliminary and many tasks remain to be solved, the classification based on basal behaviors can be an important topic for cognitive processes and computer science.
