By Radek Silhavy, Roman Senkerik, Zuzana Kominkova Oplatkova, Petr Silhavy, Zdenka Prokopova
This quantity is predicated at the learn papers offered within the 5th desktop technological know-how online Conference.
The quantity synthetic Intelligence views in clever structures provides smooth tendencies and techniques to real-world difficulties, and particularly, exploratory learn that describes novel techniques within the box of man-made intelligence. New algorithms in various fields also are presented.
The desktop technology online convention (CSOC 2016) is meant to supply a world discussion board for discussions at the most recent study ends up in all parts on the topic of desktop Science.
The addressed themes are the theoretical features and functions of computing device technological know-how, synthetic Intelligences, Cybernetics, Automation regulate conception and software program Engineering.
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Extra info for Artificial Intelligence Perspectives in Intelligent Systems: Proceedings of the 5th Computer Science On-line Conference 2016 (CSOC2016), Vol 1
44 P. Skrabanek and F. Majerík Our experiments have demonstrated that the simpliﬁed versions S1 maintain all considered metrics at values of the original detectors, both on test sets and on the real scene images. This is valid for both kernel functions, linear and RBF. Considering the results, we can positively recommend the simpliﬁed versions S1 for practical applications. Compared to the original versions, they maintain quality of the original versions and their application increase the detection speed.
Toward a History Of Epistemic Things: Synthesizing Proteins in the Test Tube. Stanford University Press, Stanford, CA (1997) 22. : Discrete Mathematics and Its Applications, 7th edn. (2011). ISBN: 0073383090 Simplified Version of White Wine Grape Berries Detector Based on SVM and HOG Features Pavel Skrabanek and Filip Majerík Abstract The detection of grapes in real scene images is a serious task solved by researches dealing with precision viticulture. Our research has shown that in the case of white wine varieties, grape berry detectors based on a support vector machine classiﬁer in combination with a HOG descriptor are very eﬃcient.
10, where S receives all sets and stores them. It is clear that S cannot be a machine and a ﬂowthing simultaneously. A (set) machine is deﬁned as a mechanism that handles (transfers, receives, processes, creates and releases) ﬂowthings. It is a contradiction that it transfers, receives, processes, creates, and releases itself. 5 Conclusion This paper proposes an abstract apparatus to represent set machines that offers a new way to view the underlying structure in set theory problems. The approach uses a diagrammatic modeling tool to produce a conceptual representation of such notions as sets, subsets, intersection, universal set, inﬁnite sets, … The resulting representation seems to introduce a new method for discussing meanings embedded in set theory.