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드론을 통한 산불 감지를 위한 효율적인 CNN 아키텍처
Hikmat Yar,Noman Khan,Fath U Min Ullah,Mi Young Lee,Sung Wook Baik 한국차세대컴퓨팅학회 2021 한국차세대컴퓨팅학회 학술대회 Vol.2021 No.05
Forest fire is one of the most dangerous disasters worldwide, due to which its management is a key concern of the research community to prevent social, ecological, and economic damages. Wildfires are extremely catastrophic disasters that lead to the destruction of forests, human assets, reduction of soil fertility and cause global warming. To overcome such kind of losses early fire detection and quick response is the key concern of research community. Therefore, in this paper, we propose a lightweight convolution neural network (CNN) method to efficiently detect the forest fire for unmanned aerial vehicles (UAVs) or drones. For the experimental evaluations, we develop an aerial images dataset from YouTube, movies, and google images. The results of the proposed architecture reveal its good performance in terms of 96% accuracy.
REMARKS ON THE INNER POWER OF GRAPHS
S. JAFARI,A.R. ASHRAFI,G.H. FATH-TABAR,M. TAVAKOLI 한국전산응용수학회 2017 Journal of applied mathematics & informatics Vol.35 No.1
Let G be a graph and k is a positive integer. Hammack and Livesay in [The inner power of a graph, Ars Math. Contemp., 3 (2010), no. 2, 193{199] introduced a new graph operation G(k), called the kth inner power of G. In this paper, it is proved that if G is bipartite then G(2) has exactly three components such that one of them is bipartite and two others are isomorphic. As a consequence the edge frustration index of G(2) is computed based on the same values as for the original graph G. We also compute the rst and second Zagreb indices and coindices of G(2).