The article discusses various methods for detecting ignition sources on aerial photographs. An algorithm based on color filtering and biorthogonal wavelet transform and the Tiny-YOLOv3 convolutional neural network were chosen for research. For the study, training and test datasets were developed. According to the results of experiments, Tiny-YOLOv3 exceeded the algorithm based on color filtering and biorthogonal wavelet transform in detection accuracy. For image processing algorithm AP was 16%. For the Tiny-YOLOv3 with input layer size of 416 × 416, the detection accuracy (AP) of fire and smoke was 56.5% and 31.9%, respectively.