Enhancing the impact of Artificial Intelligence in Medicine: A joint AIFM-INFN Italian initiative for a dedicated cloud-based computing infrastructure

Retico, Alessandra; Avanzo, Michele; Bonacorsi, D.; Botta, Francesca; Cuttone, G.; Martelli, Barbara; Salomoni, Davide; Trianni, Annalisa; Stasi, M.; Iori, Mauro; Talamonti, Cinzia

doi:10.1016/j.ejmp.2021.10.005

Cited by 10 publications

(4 citation statements)

References 72 publications

(92 reference statements)

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“…After acquiring its different states and behaviors, the tracking algorithm will be further iterated to meet the actual needs. Based on this, in the context of artificial intelligence, video surveillance will be automatically captured and analyzed by machine vision by capturing and analyzing moving objects in images or videos [27,28]. With the help of machine vision, the staff can quickly monitor and track moving targets in the scene, so as to give full play to the maximum effect of machine vision.…”

Section: R E T R a C T E D R E T R A C T E Dmentioning

confidence: 99%

Technical Research on Moving Target Monitoring and Intelligent Tracking Algorithm Based on Machine Vision

Zhou

Geng

2022

Wireless Communications and Mobile Computing

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Machine vision is an important branch of the rapid development of modern artificial intelligence, and it is a key technology to convert the image information of monitoring targets into digital signals. However, due to the wide range of machine vision applications, this research focuses on its application in video surveillance. In the era of artificial intelligence, the detection and tracking of moving objects have always been a key issue in video surveillance. The simulation of human vision is realized by combining the relevant functions of the computer and the image acquisition device, which enables the computer to have the ability to recognize the surrounding environment through images. The intelligent video analysis technology can automatically analyze and extract the key useful information from the video source with the powerful data processing ability of the computer, so as to realize the computer’s “understanding” of the video. It allows the computer to “understand” what is shown in the video or what kind of “event” happened and provides a new method and reliable basis for accident detection and accident analysis. Therefore, after a brief introduction to machine vision, moving target monitoring methods, and intelligent tracking algorithms, this paper will focus on moving target monitoring and intelligent tracking strategies for video surveillance. In addition, this paper will focus on introducing the principle of intelligent tracking algorithm through formulas and compare the accuracy and success rate of target monitoring and intelligent tracking between the machine vision-based algorithm and other algorithms during the experiment. Finally, experiments show that the monitoring and tracking effect of machine vision combined with “cloud” is the best, and the overall average can reach 85.7%. Based on this, this paper fully confirms the feasibility of the moving target monitoring and intelligent tracking algorithm based on machine vision.

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Section: R E T R a C T E D R E T R A C T E Dmentioning

confidence: 99%

Technical Research on Moving Target Monitoring and Intelligent Tracking Algorithm Based on Machine Vision

Zhou

Geng

2022

Wireless Communications and Mobile Computing

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“…INFN Cloud also integrates some ISO certificate regions used where sensitive data are stored and processed, as required by some life science and health projects [5].…”

Section: Infn Cloudmentioning

confidence: 99%

INFN and the evolution of distributed scientific computing in Italy

Salomoni,

Alkhansa,

Antonacci

et al. 2024

EPJ Web of Conf.

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INFN has been running a distributed infrastructure (the Tier-1 at Bologna-CNAF and 9 Tier-2 centres) for more than 20 years which currently offers about 150000 CPU cores and 120 PB of space both in tape and disk storage, serving more than 40 international scientific collaborations. This Grid-based infrastructure was augmented in 2019 with the INFN Cloud: a production quality multi-site federated Cloud infrastructure, composed by a core backbone, and which is able to integrate other INFN sites and public or private Clouds as well. The INFN Cloud provides a customizable and extensible portfolio offering computing and storage services spanning the IaaS, PaaS and SaaS layers, with dedicated solutions to serve special purposes, such as ISO-certified regions for the handling of sensitive data. INFN is now revising and expanding its infrastructure to tackle the challenges expected in the next 10 years of scientific computing adopting a “cloud-first” approach, through which all the INFN data centres will be federated via the INFN Cloud middleware and integrated with key HPC centres, such as the pre-exascale Leonardo machine at CINECA. In such a process, which involves both the infrastructures and the higher level services, initiatives and projects such as the "Italian National Centre on HPC, Big Data and Quantum Computing" (funded in the context of the Italian "National Recovery and Resilience Plan") and the Bologna Technopole are precious opportunities that will be exploited to offer advanced resources and services to universities, research institutions and industry. In this paper we describe how INFN is evolving its computing infrastructure, with the ambition to create and operate a national vendorneutral, open, scalable, and flexible "datalake" able to serve much more than just INFN users and experiments.

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“…Due to its long history and tradition, medical science has seen the emergence of multiple trends, schools, methods, etc. But, in the last half-century, computing and the speed in processing information are causing a qualitative leap in medical practice and research [2] , [3] , [4] . ICTs offer a scalable and multiplier infrastructure to promote continuous, intensive care and health care like never before.…”

Section: Introductionmentioning

confidence: 99%

Social influence, performance expectancy, and price value as determinants of telemedicine services acceptance in Chile

Vidal-Silva,

Sánchez-Ortiz,

Serrano-Malebrán

et al. 2024

Heliyon

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Enhancing the impact of Artificial Intelligence in Medicine: A joint AIFM-INFN Italian initiative for a dedicated cloud-based computing infrastructure

Cited by 10 publications

References 72 publications

Technical Research on Moving Target Monitoring and Intelligent Tracking Algorithm Based on Machine Vision

Technical Research on Moving Target Monitoring and Intelligent Tracking Algorithm Based on Machine Vision

INFN and the evolution of distributed scientific computing in Italy

Social influence, performance expectancy, and price value as determinants of telemedicine services acceptance in Chile

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