Results 271 to 280 of about 9,569,640 (309)

Graph-to-Graph Energy Minimization for Video Object Segmentation

Advanced Video and Signal Based Surveillance, 2019
We describe a new unsupervised video object segmentation (VOS) method based on the graph-to-graph energy minimization, which focuses on exploiting the mutual bootstrapping information between bottom-up (i.e., using pixel/superpixel attributes) and top ...
Yuezun Li, Longyin Wen, Ming-Ching Chang, Siwei Lyu   +3 more
semanticscholar   +1 more source

On the Sensitivity of Graph Energy Types

Journal of new theory
Topological indices, also known as molecular descriptors, are an indispensable tool for quantitative structure property/activity relationships models, which play a significant role in drug design processes.
M. Oz
semanticscholar   +1 more source

GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks

International Symposium on High-Performance Computer Architecture, 2021
Graph convolutional neural networks (GCNs) have emerged as an effective approach to extend deep learning for graph data analytics. Given that graphs are usually irregular, as nodes in a graph may have a varying number of neighbors, processing GCNs ...
Jiajun Li, A. Louri, Avinash Karanth, R. Bunescu   +3 more
semanticscholar   +1 more source

Other Graph Energies

2012
Motivated by the large number of interesting and nontrivial mathematical results that have been obtained for the graph energy, several other energy-like quantities were proposed and studied in the recent mathematical and mathematico–chemical literature. These are listed and briefly outlined in this chapter. Details of the theory of the main alternative
Xueliang Li, Yongtang Shi, Ivan Gutman
openaire   +1 more source

Graph Energy Based Centrality Measure to Identify Influential Nodes in Social Networks

2019 IEEE 5th International Conference for Convergence in Technology (I2CT), 2019
One of the measures to analyze complex network is vertex centrality; it can reveal existing network patterns. It helps us in understanding networks. One of the measures to analyze complex network is vertex centrality, and it can reveal existing network ...
S. Kamath, M. S
semanticscholar   +1 more source

Energy of Graphs

2020
The energy of a graph G is defined as the sum of the absolute values of the eigenvalues of its adjacency matrix. The graph energy has close correlation with the total pi-electron energy of molecules calculated with Huckel molecular orbital method in chemistry.
openaire   +1 more source

Energy-Propagation Graph Neural Networks for Enhanced Out-of-Distribution Fault Analysis in Intelligent Construction Machinery Systems

IEEE Internet of Things Journal
In intelligent fault diagnosis for construction machinery, robust and precise detection of out-of-distribution (OOD) data is crucial for enhancing operational efficiency and reducing downtime.
Xinming Li, Meng Li, Jiawei Gu, Yanxue Wang, Jiachi Yao, Jianbo Feng   +5 more
semanticscholar   +1 more source

Unicyclic Graphs with Minimal Energy

Journal of Mathematical Chemistry, 2001
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

Graph energy and topological descriptors of zero divisor graph associated with commutative ring

Journal of Applied Mathematics and Computation, 2023
Clementine Johnson, Ravi Sankar
semanticscholar   +1 more source

Pseudospectrum Energy of Graphs

2020
Let G be a simple graph of order N, the concept of resol-vent energy of graph G; i.e. ER(G)=sum_{i=1}^N (N - λi)^{-1} was established in Resolvent Energy of Graphs, MATCH commun. Math. comput. chem., 75 (2016), 279-290. In this paper we study the set of resol-vents energies of graph G which it is called pseudospectrum energy of graph PS(G).
Shelash, Hahder, Shukur, Ali
openaire   +1 more source