The article describes a feasibility study to assess the use of neural networks and traditional machine learning algorithms to solve various problems including image processing. A brief description of some algorithms of traditional machine learning, as well as an automated service for choosing the best method for a specific task, is given. The authors also describe the features of artificial neural networks and the most popular places for their application. An algorithm for solving the problem of detecting fire hazardous objects and localizing a fire source in a forest using video sequence frames is presented. The article compares the characteristics of artificial neural network models according to the following criteria: underlying architecture, the number of analyzed frames, the size of the input image, the transfer learning model used as a feature vector composing network. A comparative analysis of traditional machine learning algorithms and neural networks with long short-term memory in the problem of classification of forest fire hazards is made. A solution to localization of the source of fire based on clustering is described. A hybrid algorithm for finding a fire source in a forest is developed and illustrated.