Results 41 to 50 of about 3,331,180 (402)
IEEE Access, 2020 It is quite challenging to understand the weakest single points of failure in a network because it is the point where an entire network system can be taken down.
Mohammed Abdulaziz Al Naeem +2 more
doaj +1 more source
When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment [PDF]
IEEE wireless communicationsAI agents based on multimodal large language models (LLMs) are expected to revolutionize human-computer interaction, and offer more personalized assistant services across various domains like healthcare, education, manufacturing, and entertainment ...
Minrui Xu +7 more
semanticscholar +1 more source
On community structure validation in real networks [PDF]
Computational Statistics, 2017 Community structure is a commonly observed feature of real networks. The term refers to the presence in a network of groups of nodes (communities) that feature high internal connectivity, but are poorly connected between each other. Whereas the issue of community detection has been addressed in several works, the problem of validating a partition of ...
arxiv +1 more source
Efficient Fire Detection with E-EFNet: A Lightweight Deep Learning-Based Approach for Edge Devices
Applied Sciences, 2023 Fire detection employing vision sensors has drawn significant attention within the computer vision community, primarily due to its practicality and utility. Previous research predominantly relied on basic color features, a methodology that has since been
Haleem Farman +3 more
doaj +1 more source
Computation Diversity in Emerging Networking Paradigms [PDF]
, 2017 Nowadays, computation is playing an increasingly more important role in the future generation of computer and communication networks, as exemplified by the recent progress in software defined networking (SDN) for wired networks as well as cloud radio access networks (C-RAN) and mobile cloud computing (MCC) for wireless networks.
arxiv +1 more source
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley +1 more source
Analytical Modeling of Groups of Links in Elastic Optical Networks
IEEE AccessThis paper proposes an analytical method to determine the occupancy distribution in a group of links of elastic optical networks that service multiservice traffic streams.
Mariusz Glabowski +2 more
doaj +1 more source
IEEE Access, 2023 Recent advances in the digital gaming industry have provided impressive demonstrations of highly skilful artificial intelligence agents capable of performing complex intelligent behaviours.
Naveed Anwer Butt +6 more
doaj +1 more source
Delayed commutation in quantum computer networks
, 2005 In the same way that classical computer networks connect and enhance the capabilities of classical computers, quantum networks can combine the advantages of quantum information and communications.
C. Marand +8 more
core +1 more source
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source