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- 저자 : Chandrakala S. (검색결과 2 건)
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WIENER POLYNOMIALS AND WIENER INDICES OF THE TRANSFORMATION GRAPHS
S. B. Chandrakala,B. SOORYANARAYANA,K. Manjula,Ismail Naci CANGUL 장전수학회 2020 Advanced Studies in Contemporary Mathematics Vol.30 No.4
Topological graph indices are proven to be one of the most useful mathematical tools in the study of graphs, especially molecular graphs. Probably the most famous one is the Wiener index which was primarily used in determining the boiling points of the isomers of alkane molecules. The Wiener polynomial of G, denoted by W(G; q) is dened by W(G; q) = P fu;vgV (G) qd(u;v) where d(u; v) is the distance between the vertices u and v. The Wiener index W(G), a distance based graph invariant, is given by W(G) = P fu;vgV (G) d(u; v). In this paper, mo- tivated by the above facts, the Wiener polynomial and Wiener index of transformation graph G+++ are determined when G is isomorphic to Pn; Cn; K1;n; Kn; Wn+1, the comb and nally the tadpole graph. We have also determined the Wiener polynomial and Wiener index of trans- formation graphs Gxyz of G when G isomorphic to Pn and Cn. Finally, the formula for W(G++ ; q) is given.
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Autocorrelation of gradients based violence detection in surveillance videos
Deepak K.,Vignesh L.K.P.,Chandrakala S. 한국통신학회 2020 ICT Express Vol.6 No.3
Automated monitoring of videos is becoming mandatory due to its widespread applications over public and private domains. Especially, research over detecting anomalous human behavior in crowded scenes has created much attention among computer vision researchers. Understanding patterns in crowded scenes is always challenging due to the rapid movement of the crowd, occlusions and cluttered backgrounds. In this work, we explore spatio-temporal autocorrelation of gradient-based features to efficiently recognize violent activities in crowded scenes. A discriminative classifier is then used to recognize violent actions in videos. Experimental results have shown improved performance of the proposed approach when compared to existing state-of-art-approaches.
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