Artificial intelligence

Анотація: To increase the efficiency of monitoring data transmission in wireless networks, including sample signals and sets of frames of video data proposed in the paper is effective for the speed and accuracy of coding recognition method more informative fragments signal and image objects. The method of implementation of object-oriented and onboard tools that are part of the user’s wireless networks. For storage and transmission of reliable monitoring data in the article proposed an approach to identify the most informative complexes and fragments of signal and image object boundaries based on qualitative coding amplitude-time characteristics of significant and compelling readings bypasses of signals and video signals as well as on the determination of informative material and strong signals and video samples.

Keywords: significant samples of signals and images, informative indicators of material samples bypasses of signals and images, the selection of sites and fragments of signal and image processing, the selection of object boundaries images keyframes images

Посилання:

1. Shevchuk B.M. Technology multi-processing and data transmission in monitoring networks / B.M. Shevchuk, V.K. Zadiraka, L.A. Gnativ, S. Freier. – K. : Science. view, 2010. – 370 S.
2. Shevchuk B.M. Systematic approach to solving optimization problems by means of object computing systems Sensor Networks / B.M. Shevchuk // Information Technologies and Computer Engineering. – 2013. – No 1. – S. 88-95.
3. Nykolaychuk J.M. Information entropy measures and their application in computer systems and networks / Y.M. Nykolaychuk, A.R. Voronych // Materials of scientific interdisciplinary problem-conf. «Information problems of computer systems, law, energy, economics and modeling» (TIA-2012). – Bucac : Buchachskyy Institute of Management and Auditing, 2012. – Issue. – No 8. – S. 136-140.
4. Nykolaychuk J.M. Theory sources / Y.M. Nykolaychuk // Second edition, revised. – Ternopil : Ltd. «Ternohraf», 2010. – 536 p.
5. Bomb A.Y. Bold fuzzy fragment object images using entropy / A.J. Bomba, A. Shportko, B.J. Yaylymov, L. Shportko // Proceedings of the 2nd Ukrainian school-seminar for Young Scientists and Students «Modern Computer Information Technology», Ternopil, 4 – 5 May 2012. – Ternopol : TNEU, 2012. – S. 114-116.
6. Forsyth D.A. Computer Vision. Modern Approach / D. Forsyth, J. Pons. – M. : Yzdatelskyy house «Williams», 2004. – 928 p.
7. Dudkin А.А. Edge detection on halftone images of topological layers of integrated circuits / А.А. Dudkin, D.А. Vershok, A.M. Selihanovich // Artificial Intelligence.– 2004.– No3.– С. 453-458.
8. Zagorodnya D.I. Algorithms following up paths and selection of characteristic points in the process of segmentation of computer recognition / D.I. Zagorodnya, I.A. Pale, V.M. Krylov // Proceedings of the 3rd Ukrainian school-seminar for Young Scientists and Students : «Modern Computer Information Technology», Ternopil, May 17 – 18, 2013. – Ternopol : TNEU, 2013. – S. 129-130.
9. Boyun V.P. Comparison of two-dimensional images of objects in the form of units / V.P. Boyun, Y.A. Sabelnikov // Computer tools m networks and systems. – 2007. – No 6. – S. 155-161.