The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures Article Swipe
Marco Aldinucci
,
David Atienza
,
Federico Bolelli
,
Mónica Caballero
,
Iacopo Colonnelli
,
José Flich
,
Jon Ander Gómez
,
David González
,
Costantino Grana
,
Marco Grangetto
,
Simone Leo
,
Pedro López
,
Dana Oniga
,
Roberto Paredes
,
Luca Pireddu
,
Eduardo Quiñones
,
Tatiana Silva
,
Enzo Tartaglione
,
Marina Zapater
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1007/978-3-030-78307-5_9
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1007/978-3-030-78307-5_9
At the present time, we are immersed in the convergence between Big Data, High-Performance Computing and Artificial Intelligence. Technological progress in these three areas has accelerated in recent years, forcing different players like software companies and stakeholders to move quickly. The European Union is dedicating a lot of resources to maintain its relevant position in this scenario, funding projects to implement large-scale pilot testbeds that combine the latest advances in Artificial Intelligence, High-Performance Computing, Cloud and Big Data technologies. The DeepHealth project is an example focused on the health sector whose main outcome is the DeepHealth toolkit, a European unified framework that offers deep learning and computer vision capabilities, completely adapted to exploit underlying heterogeneous High-Performance Computing, Big Data and cloud architectures, and ready to be integrated into any software platform to facilitate the development and deployment of new applications for specific problems in any sector. This toolkit is intended to be one of the European contributions to the field of AI. This chapter introduces the toolkit with its main components and complementary tools, providing a clear view to facilitate and encourage its adoption and wide use by the European community of developers of AI-based solutions and data scientists working in the healthcare sector and others.
Related Topics
Concepts
Cloud computing
Software deployment
Exploit
Computer science
European union
Big data
Data science
Software
Key (lock)
Implementation
Field (mathematics)
Deep learning
Software engineering
Artificial intelligence
Computer security
Operating system
Pure mathematics
Economic policy
Mathematics
Business
Metadata
- Type
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- Language
- en
- Landing Page
- https://doi.org/10.1007/978-3-030-78307-5_9
- https://link.springer.com/content/pdf/10.1007/978-3-030-78307-5_9.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4293172820
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4293172820Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1007/978-3-030-78307-5_9Digital Object Identifier
- Title
-
The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud ArchitecturesWork title
- Type
-
book-chapterOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Marco Aldinucci, David Atienza, Federico Bolelli, Mónica Caballero, Iacopo Colonnelli, José Flich, Jon Ander Gómez, David González, Costantino Grana, Marco Grangetto, Simone Leo, Pedro López, Dana Oniga, Roberto Paredes, Luca Pireddu, Eduardo Quiñones, Tatiana Silva, Enzo Tartaglione, Marina ZapaterList of authors in order
- Landing page
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https://doi.org/10.1007/978-3-030-78307-5_9Publisher landing page
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https://link.springer.com/content/pdf/10.1007/978-3-030-78307-5_9.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://link.springer.com/content/pdf/10.1007/978-3-030-78307-5_9.pdfDirect OA link when available
- Concepts
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Cloud computing, Software deployment, Exploit, Computer science, European union, Big data, Data science, Software, Key (lock), Implementation, Field (mathematics), Deep learning, Software engineering, Artificial intelligence, Computer security, Operating system, Pure mathematics, Economic policy, Mathematics, BusinessTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 1, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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24Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.European | 42, 99, 156, 190 |
| abstract_inverted_index.adoption | 184 |
| abstract_inverted_index.advances | 69 |
| abstract_inverted_index.computer | 107 |
| abstract_inverted_index.immersed | 7 |
| abstract_inverted_index.intended | 150 |
| abstract_inverted_index.learning | 105 |
| abstract_inverted_index.maintain | 51 |
| abstract_inverted_index.platform | 131 |
| abstract_inverted_index.position | 54 |
| abstract_inverted_index.problems | 143 |
| abstract_inverted_index.progress | 20 |
| abstract_inverted_index.projects | 59 |
| abstract_inverted_index.quickly. | 40 |
| abstract_inverted_index.relevant | 53 |
| abstract_inverted_index.software | 34, 130 |
| abstract_inverted_index.specific | 142 |
| abstract_inverted_index.testbeds | 64 |
| abstract_inverted_index.toolkit, | 97 |
| abstract_inverted_index.Computing | 15 |
| abstract_inverted_index.community | 191 |
| abstract_inverted_index.companies | 35 |
| abstract_inverted_index.different | 31 |
| abstract_inverted_index.encourage | 182 |
| abstract_inverted_index.framework | 101 |
| abstract_inverted_index.implement | 61 |
| abstract_inverted_index.providing | 175 |
| abstract_inverted_index.resources | 49 |
| abstract_inverted_index.scenario, | 57 |
| abstract_inverted_index.solutions | 196 |
| abstract_inverted_index.Artificial | 17, 71 |
| abstract_inverted_index.Computing, | 74, 117 |
| abstract_inverted_index.DeepHealth | 81, 96 |
| abstract_inverted_index.completely | 110 |
| abstract_inverted_index.components | 171 |
| abstract_inverted_index.dedicating | 45 |
| abstract_inverted_index.deployment | 137 |
| abstract_inverted_index.developers | 193 |
| abstract_inverted_index.facilitate | 133, 180 |
| abstract_inverted_index.healthcare | 203 |
| abstract_inverted_index.integrated | 127 |
| abstract_inverted_index.introduces | 165 |
| abstract_inverted_index.scientists | 199 |
| abstract_inverted_index.underlying | 114 |
| abstract_inverted_index.accelerated | 26 |
| abstract_inverted_index.convergence | 10 |
| abstract_inverted_index.development | 135 |
| abstract_inverted_index.large-scale | 62 |
| abstract_inverted_index.applications | 140 |
| abstract_inverted_index.stakeholders | 37 |
| abstract_inverted_index.Intelligence, | 72 |
| abstract_inverted_index.Intelligence. | 18 |
| abstract_inverted_index.Technological | 19 |
| abstract_inverted_index.capabilities, | 109 |
| abstract_inverted_index.complementary | 173 |
| abstract_inverted_index.contributions | 157 |
| abstract_inverted_index.heterogeneous | 115 |
| abstract_inverted_index.technologies. | 79 |
| abstract_inverted_index.architectures, | 122 |
| abstract_inverted_index.High-Performance | 14, 73, 116 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 3 |
| institutions_distinct_count | 19 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.47999998927116394 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.76824135 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |