International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

The article examines modern artificial intelligence technologies used in photo processing, as well as their capabilities and limitations. The focus is on machine learning and deep learning algorithms that automate image editing processes, improve photo quality, and create unique artistic effects. The article also explores the ethical and technical limitations associated with the use of AI, such as processing quality, technology availability, and the impact on photographers’ creative process. The author describes the prospects for the further development of AI in the field of image processing and its potential to transform approaches to visual art. The article will be useful to both professional photographers and researchers interested in the intersection of technology and artistic expression.

A review and analysis of methods for the detection and recognition of unmanned aerial vehicles (UAVs) has been carried out. UAV detection channels were considered – acoustic, optical, radar, infrared, radio reconnaissance channel. The advantages and disadvantages of the channels used are compared and evaluated. In the case of small UAVs, there are a number of significant difficulties and limitations. One of the directions in UAV detection is acoustic observations. The noise created by the UAV’s power plant and propeller is an important unmasking feature. The creation and improvement of methods for the detection, direction-finding and recognition of small UAVs by receiving and processing their sound signals is an urgent task. In the implementation of this method of detection of UAVs are used frequency spectra, spectrograms, normalized autocorrelation functions and phase portraits of acoustic signals. Information features of the UAV sound image can be estimates of spectral coefficients determined from a discrete implementation containing a given number of samples, as well as parameters of autoregressive models.