Rabbit, toad, and the Moon: Can machine categorize them into one class?
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 4 of its 15 references that are in the map. First posted on arXiv 30 Mar 2022.
Builds on
4 of 15 references.
References · 4
- 2017AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actionscited by 449
- 2015Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classificationcited by 21
- 2017An End-to-end 3D Convolutional Neural Network for Action Detection and Segmentation in Videoscited by 6
- 2017What does a convolutional neural network recognize in the moon?cited by 2
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Citing papers per year: 2023: 1.
1 paper.