## 1 Introduction
In turn, the use of neural network algorithms seems to be the right direction due to their confirmed high effectiveness in the context of image analysis and classification. Automation of the beach line detection procedure allows for the possibility of obtaining results faster, reduces labor intensity by eliminating the need for manual image processing, and may allow for a more accurate result resistant to human error. A review of the current state of knowledge demonstrated the broad range of potentials for the application of unmanned aerial vehicles (UAVs) and data processing in the mining industry. This technology is becoming increasingly common and mature in both developed and developing countries. UAVs are used in open-pit, underground, and closed mines [14; 15; 16; 17; 18]. They are particularly useful in small mines, where expensive surveying equipment or professional expertise is often lacking [19]. It is worth noting that with the advent of UAVs, various sensors have become more miniaturized and intelligent. UAVs offer numerous advantages, including low cost, flexibility, and high precision. However, the main limitations of UAVs are battery life, harsh working environments (especially in underground mining), weather and lighting conditions, and local regulations and laws [20; 21; 22; 23]. One of the applications of UAVs in the mining industry is topographic control. In [24], the authors compared conventional technologies with photogrammetry in a small open-pit mine in southern Brazil. The results showed that the level of detail achieved by UAV photogrammetry methods is more accurate, denser in information, and faster compared to traditional techniques, such as GPS point measurements or laser scanning. Given that the active mining area is characterized by constant material movement, numerous surface irregularities, and scattered material, the authors deemed the recorded height differences acceptable within the range of variability. The assessment of stability and deformation behavior of high rock slopes was the subject of research in [25]. The study used a remote sensing approach to characterize rock slopes at different scales and distances, critical for detecting failure mechanisms. The research demonstrated that UAV datasets are effective in performing structural and geomorphological characterization of large-scale areas. The methodology for creating a 3D model of an open-pit mine based on UAV imagery was described in [26]. The article explains how digital images and photogrammetry techniques can be used to develop accurate 3D geometric models. It highlights the potential use of information contained in the 3D model within a GIS environment, including process monitoring, obtaining geometric information about embankments, slopes, road infrastructure, and planning logistical and operational processes. A similar application of low-cost digital photogrammetry for monitoring and documenting terrain surfaces affected by mining activities was described in [19]. The study assessed the accuracy of the digital elevation model (DEM) obtained from UAV photogrammetry in a Slovak open-pit mine case study. The DEM accuracy was deemed acceptable by national regulatory standards. In [27], a rapid and low-cost method for monitoring, the geomorphological changes occurring over years in open-pit mines were presented. The authors proposed using the structure-from-motion photogrammetric technique to build high-resolution digital elevation models (DEMs). The developed procedure allows for the quantitative estimation of area changes (volumetric changes and extracted tonnage) and the assessment of terrace alterations and the surface extent of the open-pit mine. The authors highlighted the method's potential for evaluating slope stability and identifying hazards such as landslides. Other examples of using drones for DEM construction can be found in the works of [PERSON] et al. [28; 29; 30]. In [31], the use of Unmanned Aerial Systems (UAS) to bridge the gap between spectral data from satellites or aircraft and ground data is described.