veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System

@inproceedings{Amir2022veriFIREVA,
  title={veriFIRE: Verifying an Industrial, Learning-Based Wildfire Detection System},
  author={Guy Amir and Ziv Freund and Guy Katz and Elad Mandelbaum and Idan Refaeli},
  booktitle={World Congress on Formal Methods},
  year={2022}
}
In this short paper, we present our ongoing work on the veriFIRE project -- a collaboration between industry and academia, aimed at using verification for increasing the reliability of a real-world, safety-critical system. The system we target is an airborne platform for wildfire detection, which incorporates two deep neural networks. We describe the system and its properties of interest, and discuss our attempts to verify the system's consistency, i.e., its ability to continue and correctly… 
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