Zobrazeno 1 - 10
of 224
pro vyhledávání: '"Rami Abielmona"'
Publikováno v:
Global Epidemiology, Vol 8, Iss , Pp 100168- (2024)
Background: Research comparing artificial intelligence and machine learning (AI/ML) methods with classical statistical methods applied to large population health databases is limited. Objectives: This retrospective cohort study aimed to compare the p
Externí odkaz:
https://doaj.org/article/90cd181a34b448cf91b0d9d86b49ac8e
Publikováno v:
IEEE Instrumentation & Measurement Magazine. 24:118-126
This article elaborates on how machine learning (ML) can leverage the solution of a contemporary problem related to the security of maritime domains. The worldwide ``Illegal, Unreported, and Unregulated'' (IUU) fishing incidents have led to serious e
Publikováno v:
2021 IEEE Symposium Series on Computational Intelligence (SSCI).
Publikováno v:
2020 IEEE International Systems Conference (SysCon).
In this paper, we propose and adapt decision model formulations and algorithms suitable to the distributed satellite collection tasking problem. The decentralized multi-satellite scheduling problem setting comprises multiple stakeholders having contr
Autor:
Bijan Raahemi, Rafael Falcon, Ibrahim Abualhaol, Fatemeh Cheraghchi, Emil M. Petriu, Rami Abielmona
Publikováno v:
Information Sciences. :53-74
Liner shipping is vulnerable to many disruptive factors such as port congestion or harsh weather, which could result to delay in arriving at the ports. It could result in both financial and reputation losses. The vessel schedule recovery problem (VSR
Publikováno v:
IEEE Communications Surveys & Tutorials. 20:2822-2854
Wireless sensor and actuator networks (WSANs) are heterogeneous networks composed of many different nodes that can cooperatively sense the environment, determine an appropriate action to take, then change the environment’s state after acting on it.
Publikováno v:
AVSS
This paper describes multi-component spatiotemporal attention mechanisms in application to object detection in videos. The detection of objects of interest relies on the analysis of feature-point areas (FPAs), which correspond to the object-relevant
Publikováno v:
GECCO (Companion)
A new framework1 mixing evolutionary approach, discrete-event simulation and deep neural networks is proposed to achieve multi-asset collection/image acquisition scheduling in a surveillance context. It combines an extended graph-based hybrid genetic
Publikováno v:
2019 22th International Conference on Information Fusion (FUSION).
Publikováno v:
Uncertainty Management with Fuzzy and Rough Sets ISBN: 9783030104627
This chapter uses genetic fuzzy systems (GFS) to assess the risk level of maritime vessels transmitting Automatic Identification System (AIS) data. Previous risk assessment approaches based on fuzzy inference systems (FIS) relied on domain experts to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51a90fff13748a9f9066092ba4f220fd
https://doi.org/10.1007/978-3-030-10463-4_19
https://doi.org/10.1007/978-3-030-10463-4_19