Зменшення кількості хибних викликів під час розв’язання задачі детектування полум'я у відеопотоці з використанням глибоких згорткових нейронних мереж
In this paper, we develop a new approach for detecting fire in images based on convolutional neural networks. Cascade structure, which provides improved efficiency of recognition in images with low resolution and objects that can visually resemble flames, was proposed. We have performed an experimental comparison with the modern method of objects detecting Faster R-CNN. As a result of the experiments, it was found that performance of fire recognition improved on average by 20%.