Detection

Information System for Geolocation Detection and Tracking of Military Facilities

The article presents an information system that automatically detects military objects in images or video streams, determines their exact geographic coordinates, and tracks their future movements through data visualization. The development of such a system is an extremely relevant task in the context of modern threats, as it can significantly enhance military units' situational awareness and improve operational planning. During the research, existing approaches to object detection, geolocation methods, and target tracking algorithms were analyzed.

DeepFaceEmotion: Enhancing Emotion Detection through Transfer Learning and Convolutional Neural Networks

Emerging as a crucial tool for companies in many industries, emotion recognition offers a greater understanding of consumer views of goods and services, hence strengthening client connections, improving service delivery, and guiding emotionally intelligent marketing strategies.  Particularly with the use of transfer learning techniques, end-to-end image-based emotion categorization has gained popularity in the last several years.  In tackling such challenging tasks, deep learning models have shown great efficacy.  Though reading emotions from visual data presents diffic

Advanced text-based transformer architecture for malicious social bots detection

The increasing prevalence of automated social media accounts, or Social Media Bots (SMBs), presents significant challenges in maintaining authentic online discourse and preventing disinformation campaigns on social platforms.  This research introduces a novel multiclass classification framework for detecting and categorizing SMBs, leveraging fine-tuned transformer-based models.  In this study, we conducted a comprehensive comparative analysis of various transformer variants, including BERT, DistilBERT, RoBERTa, DeBERTa, XLNet, and ALBERT, to evaluate their efficacy in r

DEVELOPMENT OF A MODEL OF A CYBER THREATS DETECTION SYSTEM WITH SUPPORT AND UPDATE OF ATTACK DETECTION RULES

The article addresses the issue of data protection in information and communication systems amid the growing volume of traffic and the increasing number of cyber threats, necessitating improvements in the effectiveness of intrusion detection and prevention systems. Various types of Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS), their advantages, and disadvantages are considered. The methods of threat detection are analyzed, including signature-based methods, anomaly detection methods, and machine learning-based methods.

Total and partial observation–detection in linear dynamical systems with characterized sources: finite-dimensional cases

In this work, we address the partial observation–detection problem for finite-dimensional dynamical linear systems that may not be fully observable or detectable.  We introduce the concepts of `observation–detection' and `partial observation–detection,' which involve reconstructing either the entirety or a portion of the system state and the source reacting on the system, even when the system is not fully observable or detectable.  We provide characterizations of `observable–detectable systems' and `observable–detectable spaces.'  The reconstruction of the state and sou

Feature of detection and realization of investigative actions on the start-up period investigation of drugs’ smuggling

In this article explores the features of detection and realization of investigative actions on the start-up period of investigation contraband smuggling of narcotics , psychotropic substances and falsification medicinal means .The algorithm of operating is offered on the start-up period of investigation of this crime