Перегляд за Автор "Vit, R."

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  • Ескіз
    Документ
    Intelligent System for Determining the Object Attributes Values by Neural Networks Means by Graphic Images in Databases
    (2024) Mazurets, O.; Uspenska, K.; Vit, R.; Tyschenko, O.; Мазурець, Олександр Вікторович
    The created method for determining the values of object attributes is designed to convert input data in the form of a video stream and a fixation frequency indicator into output data in the form of a list of values of actual object attributes in the database by obtaining a frame for processing from the video stream, receiving an object image for recognition from the frame, and determining the value of the object attribute from the image.
  • Ескіз
    Документ
    Investigation of Neural Network Detecting of Construction Waste by Photos
    (2025) Mazurets, O.; Ovcharuk, O.; Vit, R.; Мазурець, Олександр Вікторович
    This paper presents a practice-oriented investigation of neural architectures for visual recognition of construction and demolition (C&D) waste in realistic conditions. We study a two-stage pipeline that first localizes candidate fragments on a scene and then assigns materialspecific labels, emphasizing data curation, restrained augmentation, and evaluation protocols aligned with production constraints. Results indicate that coupling a single-shot detector with per class residual classifiers improves recall on visually confusable materials while preserving precision, offering a pragmatic path toward reliable sorting-line deployment.
  • Ескіз
    Документ
    Practical Application of Method of Thematic Classification of Text Information Using LDA
    (2024) Mazurets, O.; Vit, R.; Мазурець, Олександр Вікторович
    Method of thematic classification of textual information has been developed, examples of the analysis of the effectiveness of the created method on an English-language data set using the corresponding developed software are given. From the thematic modeling in the dataset, as a result of applying the method, a cross-validation check was carried out, which gave a result of 0.86, which is an improvement of 0.15 in comparison with the use of LDA in its pure form for classification
  • Ескіз
    Документ
    Practical Approach for Detection by Deep Learning of Target Objects of Subject Area Based on Semantic Connectivity Indicators in Audio Database
    (2024) Mazurets, O.; Sobko, O.; Vit, R.; Pasternak, V.; Мазурець, Олександр Вікторович
    A practical approach for detection was performed by deep learning of target objects in the subject area based on semantic connectivity indicators in an audio database. A database was also created for the software that detects actors in Ukrainian-language audio data for the media sphere. This database includes the necessary tables that provide convenient storage and organization of information about actors, audio data and transcription. It is a key tool for analysing and processing audio data in the media field, which allows you to efficiently identify, classify and analyze the information contained in audio files, taking into account their context and content.