Browsing 2024 International Conference "Electrical, Electronic and Information Sciences“ (eStream) by Institution "Kharkiv National University of Radio Electronics"

Now showing items 1-5 of 5

    • AI Models of Pulmonary Sarcoidosis Detection 

      Shcherban, Yaroslav; Kyrylo, Smelyakov; Chupryna, Anastasiya (2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), April 25, 2024, Vilnius, Lithuania, 2024)
      Sarcoidosis, a multifaceted inflammatory disorder, often involves the ′ lungs, presenting challenges in diagnosis and management. Computed tomography (CT) imaging is pivotal in assessing pulmonary sarcoidosis, yet ...

    • Comparison of Object Detection Algorithms for the Task of Person Detection on Jetson TX2 NX Platform 

      Byzkrovnyi, Oleksandr; Smelyakov, Kyrylo; Chupryna, Anastasiya; Lanovyy, Oleksiy (2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), April 25, 2024, Vilnius, Lithuania, 2024)
      This article is an investigation for the best suited algorithm for object detection on Jetson TX2 NX platform. Previous research aimed at determination of the quickest and the most accurate algorithm for obj ect detection ...

    • Deepfake Detection Models Based on Machine Learning Technologies 

      Smelyakov, Kirill; Kitsenko, Yuriy; Chupryna, Anastasiya (2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), April 25, 2024, Vilnius, Lithuania, 2024)
      The paper is devoted to efficiency evaluation of modern deepfake detection models based on convolutional neural networks (CNN). In the context of rapid development of digital technologies and increasing volume of information ...

    • Free DBMSs Performance for an Inventory Management System based on Spring Boot 

      Guzhov, Viacheslav; Smelyakov, Kyrylo (2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), April 25, 2024, Vilnius, Lithuania, 2024)
      This research examines the integration of free Database Management Systems (DBMSs) with a Spring Bootdriven Inventory Management System. Evaluating MySQL, PostgreSQL, MongoDB, and SQLite, the study explores performance ...

    • Hybrid Neural Network Classifier for Detecting Weeds and Plant Diseases in Greenhouses 

      Chaikovskyi, Serhii; Smelyakov, Sergey (2024 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), April 25, 2024, Vilnius, Lithuania, 2024)
      Greenhouse farming plays a crucial role in satisfying the demand throughout the year, regardless of climatic conditions. However, maintaining crop health in greenhouses is critical and challenging. This paper is devoted ...