| DC Field | Value | Language |
|---|
| dc.contributor.author | Rudchick, Illya | |
| dc.contributor.author | Basyuk, Taras | |
| dc.coverage.temporal | 23-24 April 2020, Lviv, Ukraine | |
| dc.date.accessioned | 2020-06-12T11:09:37Z | - |
| dc.date.available | 2020-06-12T11:09:37Z | - |
| dc.date.created | 2020-04-23 | |
| dc.date.issued | 2020-04-23 | |
| dc.identifier.citation | Rudchick I. The Object Recognition System in the Video Stream / Illya Rudchick, Taras Basyuk // Computational linguistics and intelligent systems : proceedings of the 4nd International conference, 23-24 April 2020, Lviv, Ukraine. — Lviv : Lviv Politechnic Publishing House, 2020. — Vol 2 : Proceedings of the 4nd International conference, COLINS 2020. Workshop, Lviv, Ukraine April 23-24, 2020. — P. 141–144. — (Intelligent Systems). | |
| dc.identifier.issn | 2523-4013 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52122 | - |
| dc.description.abstract | The article describes the analysis of known approaches and systems
of pattern recognition, shows their shortcomings and shows the relevance of
this task. The system using a structural approach was designed and a software
tool that implements the process of object recognition in the video stream was developed. | |
| dc.format.extent | 141-144 | |
| dc.language.iso | en | |
| dc.publisher | Видавництво Львівської політехніки | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Computational linguistics and intelligent systems : proceedings of the 4nd International conference (2), 2020 | |
| dc.relation.uri | https://www.learnopencv.com/opencv-c-vs-python-vs-matlab-for-computer-vision | |
| dc.subject | Computer vision | |
| dc.subject | object recognition | |
| dc.subject | motion detection | |
| dc.subject | noise cancellation | |
| dc.title | The Object Recognition System in the Video Stream | |
| dc.type | Article | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2020 | |
| dc.contributor.affiliation | Lviv Polytechnic National University | |
| dc.format.pages | 4 | |
| dc.identifier.citationen | Rudchick I. The Object Recognition System in the Video Stream / Illya Rudchick, Taras Basyuk // Computational linguistics and intelligent systems : proceedings of the 4nd International conference, 23-24 April 2020, Lviv, Ukraine. — Lviv : Lviv Politechnic Publishing House, 2020. — Vol 2 : Proceedings of the 4nd International conference, COLINS 2020. Workshop, Lviv, Ukraine April 23-24, 2020. — P. 141–144. — (Intelligent Systems). | |
| dc.relation.references | 1. Tufte, E. (2001) The Visual Display of Quantitative Information / E. Tufte. Second edition. Connecticut: Graphics Press, 206p. | |
| dc.relation.references | 2. Dix, A.(2009) Human-Computer Interaction / A. Dix. New York, USA: Springer US, P. 1327–1331. | |
| dc.relation.references | 3. OpenCV (C++ vs Python) vs MATLAB for Computer Vision [Electronic source] / Access mode: https://www.learnopencv.com/opencv-c-vs-python-vs-matlab-for-computer-vision. | |
| dc.relation.references | 4. Demchuk, A., Lozynska, O.: The Typhlocomments Rules for Audiodescription System of the Video Content Formation for People with Visual Impairments. In: Computational Linguistics and Intelligent Systems, COLINS, 2, 53-59. (2018) | |
| dc.relation.references | 5. Lytvyn, V., Vysotska, V., Mykhailyshyn, V., Rzheuskyi, A., Semianchuk, S.: System Development for Video Stream Data Analyzing. In: Advances in Intelligent Systems and Computing, 1020, 315-331. (2020) | |
| dc.relation.references | 6. Veres, O., Rishnyak, I., Rishniak, H.: Application of Methods of Machine Learning for the Recognition of Mathematical Expressions. In: Computational linguistics and intelligent systems, COLINS, 378-389. (2019) | |
| dc.relation.references | 7. Bakumenko, N., Strilets, V., Ugryumov, M.: Application of the C-Means Fuzzy Clustering Method for the Patient's State Recognition Problems in the Medical Monitoring System. In: Computational linguistics and intelligent systems, COLINS, 218-227. (2019) | |
| dc.relation.references | 8. Dovbysh, A., Shelehov, I., Pylypenko, S., Berest, O.: Estimation of Informativeness of Recognition Signs at Extreme Information Machine Learning of Knowledge Control System. In: Computational linguistics and intelligent systems, COLINS, 143-152. (2019) | |
| dc.relation.references | 9. Dovbysh, A., Alieksieiev, V.: Embedding Speech Recognition Tools for Custom Software: Engines Overview. In: Computational Linguistics and Intelligent Systems, COLINS, 2, 114-121. (2018) | |
| dc.relation.references | 10. Lytvyn, V., Vysotska, V., Pukach, P., Bobyk, І., Uhryn, D.: Development of a method for the recognition of author’s style in the Ukrainian language texts based on linguometry, stylemetry and glottochronology. In: Eastern-European Journal of Enterprise Technologies, 4(2-88), 10-19. (2017) | |
| dc.relation.references | 11. Lytvyn, V., Peleshchak, I., Vysotska, V., Peleshchak, R.: Satellite spectral information recognition based on the synthesis of modified dynamic neural networks and holographic data processing techniques. In: Proceedings of the International Conference on Computer Sciences and Information Technologies, CSIT, 330-334. (2018) | |
| dc.relation.references | 12. Zdebskyi, P., Vysotska, V., Peleshchak, R., Peleshchak, I., Demchuk, A., Krylyshyn, M.: An Application Development for Recognizing of View in Order to Control the Mouse Pointer. In: CEUR Workshop Proceedings, Vol-2386, 55-74. (2019) | |
| dc.relation.references | 13. Shu, C., Dosyn, D., Lytvyn, V., Vysotska V., Sachenko, A., Jun, S.: Building of the Predicate Recognition System for the NLP Ontology Learning Module. In: International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS, 2, 802-808. (2019) | |
| dc.relation.referencesen | 1. Tufte, E. (2001) The Visual Display of Quantitative Information, E. Tufte. Second edition. Connecticut: Graphics Press, 206p. | |
| dc.relation.referencesen | 2. Dix, A.(2009) Human-Computer Interaction, A. Dix. New York, USA: Springer US, P. 1327–1331. | |
| dc.relation.referencesen | 3. OpenCV (C++ vs Python) vs MATLAB for Computer Vision [Electronic source], Access mode: https://www.learnopencv.com/opencv-c-vs-python-vs-matlab-for-computer-vision. | |
| dc.relation.referencesen | 4. Demchuk, A., Lozynska, O., The Typhlocomments Rules for Audiodescription System of the Video Content Formation for People with Visual Impairments. In: Computational Linguistics and Intelligent Systems, COLINS, 2, 53-59. (2018) | |
| dc.relation.referencesen | 5. Lytvyn, V., Vysotska, V., Mykhailyshyn, V., Rzheuskyi, A., Semianchuk, S., System Development for Video Stream Data Analyzing. In: Advances in Intelligent Systems and Computing, 1020, 315-331. (2020) | |
| dc.relation.referencesen | 6. Veres, O., Rishnyak, I., Rishniak, H., Application of Methods of Machine Learning for the Recognition of Mathematical Expressions. In: Computational linguistics and intelligent systems, COLINS, 378-389. (2019) | |
| dc.relation.referencesen | 7. Bakumenko, N., Strilets, V., Ugryumov, M., Application of the C-Means Fuzzy Clustering Method for the Patient's State Recognition Problems in the Medical Monitoring System. In: Computational linguistics and intelligent systems, COLINS, 218-227. (2019) | |
| dc.relation.referencesen | 8. Dovbysh, A., Shelehov, I., Pylypenko, S., Berest, O., Estimation of Informativeness of Recognition Signs at Extreme Information Machine Learning of Knowledge Control System. In: Computational linguistics and intelligent systems, COLINS, 143-152. (2019) | |
| dc.relation.referencesen | 9. Dovbysh, A., Alieksieiev, V., Embedding Speech Recognition Tools for Custom Software: Engines Overview. In: Computational Linguistics and Intelligent Systems, COLINS, 2, 114-121. (2018) | |
| dc.relation.referencesen | 10. Lytvyn, V., Vysotska, V., Pukach, P., Bobyk, I., Uhryn, D., Development of a method for the recognition of authors style in the Ukrainian language texts based on linguometry, stylemetry and glottochronology. In: Eastern-European Journal of Enterprise Technologies, 4(2-88), 10-19. (2017) | |
| dc.relation.referencesen | 11. Lytvyn, V., Peleshchak, I., Vysotska, V., Peleshchak, R., Satellite spectral information recognition based on the synthesis of modified dynamic neural networks and holographic data processing techniques. In: Proceedings of the International Conference on Computer Sciences and Information Technologies, CSIT, 330-334. (2018) | |
| dc.relation.referencesen | 12. Zdebskyi, P., Vysotska, V., Peleshchak, R., Peleshchak, I., Demchuk, A., Krylyshyn, M., An Application Development for Recognizing of View in Order to Control the Mouse Pointer. In: CEUR Workshop Proceedings, Vol-2386, 55-74. (2019) | |
| dc.relation.referencesen | 13. Shu, C., Dosyn, D., Lytvyn, V., Vysotska V., Sachenko, A., Jun, S., Building of the Predicate Recognition System for the NLP Ontology Learning Module. In: International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS, 2, 802-808. (2019) | |
| dc.citation.spage | 141 | |
| dc.citation.epage | 144 | |
| dc.coverage.placename | Львів | |
| dc.coverage.placename | Lviv | |
| Appears in Collections: | Computational linguistics and intelligent systems. – 2020 р.
|
