The integration of machine learning technologies into print quality control systems represents a significant advancement in modern printing production. This article examines the application of artificial intelligence methods and computer vision algorithms for automated defect detection, colour consistency monitoring, and real-time quality assessment in printing processes.
The article considers methods and means of face recognition in a video data stream using elements of machine learning. The main approaches to face identification based on computer vision methods are analyzed, in particular the principal component analysis (PCA) method, the local binary pattern analysis (LBP) method and the linear discriminant analysis (LDA, Fisherfaces) method. The principles of facial feature formation and algorithms for their classification are described.
The paper addresses the problem of improving the accuracy of automated object detection in thermal images under conditions of low contrast, sensor noise, and structural uncertainty of the terrain. The relevance of this research is driven by the increasing use of unmanned aerial vehicles for monitoring and reconnaissance, where thermal imaging systems serve as a key source of information in low-visibility environments.
This paper addresses the current problem of flight planning in swarm systems of mobile sensor platforms with an integrated system for detecting camouflaged objects in complex observation environments. Considering the rapid increase in data volumes received from distributed sensor agents, as well as high requirements for accuracy and operational decision-making, a comprehensive approach to dynamic acquisition, processing, and recognition of three-dimensional images of structural objects is proposed.
Night vision devices (NVD) and thermal imaging cameras are widely used in the fields of surveillance, security and monitoring, search and rescue, emergency response, industrial control and maintenance, ground operations and unmanned aerial vehicles. Night vision devices operate on the principle of amplifying residual light (starlight, moonlight, city lighting) in the visible and near-infrared ranges (0.4–0.9 μm). Thermal imaging devices record thermal radiation of objects in the medium (3–5 μm) or far (8–14 μm) infrared range.
A high-precision method for predicting the linear dimensions of three-dimensional objects of arbitrary shape based on computed tomography data has been developed. The method is aimed at reducing measurement errors caused by partial-volume effects, shadow transitions, and arbitrary spatial orientation of the object.
Resume parsing is a method used to extract key information from resumes, allowing for further actions such as candidate selection and ranking. In traditional recruitment processes, companies often handle thousands of resumes manually or require applicants to follow a pre-defined template. However, the evolving recruitment environment calls for more advanced technological solutions and efficient resume analysis methods. Although various basic techniques can analyze structured documents, they are inadequate for processing unstructured formats such as PDF, DOC, and DOCX
Autonomous navigation of unmanned aerial vehicles (UAVs) in unstructured industrial environments remains challenging due to irregular geometry, dynamic obstacles and sensor uncertainty. Classical Simultaneous Localization and Mapping (SLAM) systems, though geometrically consistent, often fail under poor initialization, textureless areas or reflective surfaces. To overcome these issues, this work proposes a hybrid transformer-geometric framework that fuses learned scene priors with keyframe-based SLAM.
In today’s world of globalized trade and ecommerce, product labeling is becoming increasingly important. It ensures product traceability throughout the supply chain, provides information and protection, and influences consumer confidence. Traditional methods of checking and reading labels are based on manual control or the use of simple barcode scanners, which often prove ineffective in conditions of increasing data processing volumes.
The goal of the article is to provide a methodology of improving images quality in low-light conditions trough fusion of data received from telecamera and thermal camera. Data from thermal camera uses for compensation of significant illumination reduction in poor lighting conditions and allow keep required level of information. Proposed method establishes dynamic regulation of fusion coefficients depending on brightness level to minimize artifacts, increase edge sharpness, and improve object detectability.