Abstract:
As a new fire detection technolog}, image fire detection has recentlv played a
important role in reducing fire losses by alarming users early through early fire
detection. Image fire detection is based on an algorithmic analysis ofimages. However,
there is a lower accuracy, delayed detection, and a large amount of computation in
common detection algorithms, including manually and machine automatical!}
extracting image features. Therefore, novel image fire detection algorithms based on
the advanced object detection CNN models. A comparison between proposed and
current systems reveals that the accuracy of fire detection algorithms is depend on
object detection CNNs is higher than other algorithms. We use TensorFlow in our
piv>wL iensorFlo,. i> a P}thon library for fast numerical computing created arJ
released by Googie. It is a foundation library that can be used to create Deep Lcv.nimg
models direct!} or by using wrapper libraries that simplify the process built on ton
TensorFlow.
