Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Travencolo, Bruno A. N."'
Temporal graphs represent interactions between entities over time. These interactions may be direct, a contact between two vertices at some time instant, or indirect, through sequences of contacts called journeys. Deciding whether an entity can reach
Externí odkaz:
http://arxiv.org/abs/2306.13937
Autor:
Santos, Dalí F. D. dos, de Faria, Paulo R., Loyola, Adriano M., Cardoso, Sérgio V., Travençolo, Bruno A. N., Nascimento, Marcelo Z. do
Computer-aided diagnosis (CAD) can be used as an important tool to aid and enhance pathologists' diagnostic decision-making. Deep learning techniques, such as convolutional neural networks (CNN) and fully convolutional networks (FCN), have been succe
Externí odkaz:
http://arxiv.org/abs/2303.10172
Temporal graphs model relationships among entities over time. Recent studies applied temporal graphs to abstract complex systems such as continuous communication among participants of social networks. Often, the amount of data is larger than main mem
Externí odkaz:
http://arxiv.org/abs/2204.12468
Temporal graphs represent interactions between entities over the time. These interactions may be direct (a contact between two nodes at some time instant), or indirect, through sequences of contacts called temporal paths (journeys). Deciding whether
Externí odkaz:
http://arxiv.org/abs/2102.04187
Visual analysis of temporal networks comprises an effective way to understand the network dynamics, facilitating the identification of patterns, anomalies, and other network properties, thus resulting in fast decision making. The amount of data in re
Externí odkaz:
http://arxiv.org/abs/2009.11422
One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the rec
Externí odkaz:
http://arxiv.org/abs/0902.3068
Akademický článek
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The importance of structured, complex connectivity patterns found in several real-world systems is to a great extent related to their respective effects in constraining and even defining the respective dynamics. Yet, while complex networks have been
Externí odkaz:
http://arxiv.org/abs/0805.2298
In this work we propose the use of a hirarchical extension of the polygonality index as a means to characterize and model geographical networks: each node is associated with the spatial position of the nodes, while the edges of the network are define
Externí odkaz:
http://arxiv.org/abs/0706.3975
Akademický článek
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