关键词: 火灾检测, 特征工程, 残差网络, 特征金字塔网络

Abstract:

The traditional fire detection algorithm relies on artificial feature engineering, which is subjective and blind. It has the problems of poor generalization ability and low detection accuracy. In this paper, a fire image detection algorithm based on improved Mask R-CNN is proposed. On the basis of Mask R-CNN, the algorithm introduces a bottom-up feature fusion in the feature pyramid, and improves the loss function to make the frame location more accurate. Experiments on the self-built test dataset show that the accuracy of the improved algorithm is higher than that of the original algorithm, and the detection accuracy is increased by more than 5%.

Key words: fire detection, feature engineering, residual network, Feature Pyramid Network（FPN）