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Predicting Geographic Information with Neural Cellular Automata

2020-09-20 · Mingxiang Chen, Qichang Chen, Lei Gao, Yilin Chen, Zhecheng Wang

This paper presents a novel framework using neural cellular automata (NCA) to regenerate and predict geographic information. The model extends the idea of using NCA to generate/regenerate a specific image by training the model with various geographic data, and thus, taking the traffic condition map as an example, the model is able to predict traffic conditions by giving certain induction information. Our research verified the analogy between NCA and gene in biology, while the innovation of the model significantly widens the boundary of possible applications based on NCAs. From our experimental results, the model shows great potentials in its usability and versatility which are not available in previous studies. The code for model implementation is available at https://redacted.

📄 PDF Abstract BibTeX arXiv:2009.09347

Code (1)

chenmingxiang110/NCA_Prediction pytorch

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