Fraunhofer-Publica

The Fraunhofer-Publica has been successfully documenting the research results of the Fraunhofer-Gesellschaft for over 30 years. The platform enables the collaborative linking of research-relevant objects and disseminates within the international scientific community.

The Fraunhofer-Publica thus fulfils its responsibility to promote the transfer of knowledge and know-how to industry and society.

Categories

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Research outputs

As an application-oriented research organisation, Fraunhofer aims to conduct highly innovative and solution-oriented research - for the benefit of society and to strengthen the German and European economy.

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Projects

Fraunhofer is tackling the current challenges facing industry head on. By pooling their expertise and involving industrial partners at an early stage, the Fraunhofer Institutes involved in the projects aim to turn original scientific ideas into marketable products as quickly as possible.

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Researchers

Scientific achievement and practical relevance are not opposites - at Fraunhofer they are mutually dependent. Thanks to the close organisational links between Fraunhofer Institutes and universities, science at Fraunhofer is conducted at an internationally first-class level.

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Institutes

The Fraunhofer-Gesellschaft is the leading organisation for applied research in Europe. Institutes and research facilities work under its umbrella at various locations throughout Germany.

Recent Additions

  • Publication
    Artificial Intelligence Applications for Resilience in Manufacturing - A Systematic Literature Review
    ( 2024)
    Maier, Florian
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    Puppala, Sivaphani
    ;
    Oberle, Michael
    This review provides a structured literature analysis of Artificial Intelligence (AI) applications in enhancing manufacturing resilience. The research is guided by three primary questions addressing the use cases, technologies, and benefits of AI across the five resilience phases: Prepare, Prevent, Protect, Respond, and Recover. Findings from 78 papers reveal that AI significantly contributes to predictive maintenance, risk mitigation, and quality control, with machine learning and deep learning being the predominant technologies. The study highlights the pivotal role of AI in advancing manufacturing towards proactive, resilient, and adaptable operations. The insights gleaned offer a roadmap for future research and practical AI integration in manufacturing, underscoring the value of AI in driving industrial innovation and efficiency.
  • Publication
    Forschungs-, Technologie- und Innovationspolitik muss die Entstehung kritischer Massen fördern
    ( 2024)
    Schubert, Torben orcid-logo
    ;
    Kroll, Henning orcid-logo
    ;
    Blind, Knut orcid-logo
    ;
    Frietsch, Rainer
    Economic research emphasises the role of increasing returns to scale and critical mass in research and technology development. This suggests that countries benefit from specialising in certain technologies and can thereby bundle available resources. Using the example of the Exzellenzstrategie and the Zukunftsstrategie, we argue that German RTI policy lacks strategic prioritisation. The lack of focus implies that Germany spreads its resources too thinly over many technological alternatives and therefore fails to create critical mass within each of them. The guiding principles for a German RTI policy should focus on creating critical mass through specialisation
  • Publication
    2nd Workshop on Maritime Computer Vision (MaCVi) 2024: Challenge Results
    ( 2024)
    Kiefer, Benjamin
    ;
    Žust, Lojze
    ;
    Kristan, Matej
    ;
    Perš, Janez
    ;
    Teršek, Matija
    ;
    Wiliem, Arnold
    ;
    Messmer, Martin
    ;
    Yang, Cheng
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    Huang, Wei
    ;
    Jiang, Zhongyu
    ;
    Kuo, Cheng-liang
    ;
    Mei, Jie
    ;
    Hwang, Jenq-neng
    ;
    Stadler, Daniel
    ;
    Sommer, Lars Wilko
    ;
    Huang, Kaer
    ;
    Aiguo Zheng
    ;
    Chong, Weitu
    ;
    Lertniphonphan, Kanokphan
    ;
    Xie, Lie-jun
    ;
    Chen, Feng
    ;
    Li, Jian
    ;
    Wang, Zhepeng
    ;
    Zedda, Luca
    ;
    Loddo, Andrea
    ;
    Di Ruberto, Cecilia
    ;
    Vu, Tuan-Anh
    ;
    Hai, Nguyen
    ;
    Ha, Van Sang
    ;
    Tien, Dung Pham
    ;
    Yeung, Kit Ling
    ;
    Feng, Yuan
    ;
    Thien, Nguyen Thanh
    ;
    Tian, Lixin
    ;
    Kuan, Sheng-Yao
    ;
    Ho, Yuan-Hao
    ;
    Bueno Rodriguez, Angel
    ;
    Carrillo-Perez, Borja
    ;
    Klein, Alexander
    ;
    Alex, Antje
    ;
    Steiniger, Yannik
    ;
    Sattler, Felix
    ;
    Solano-carrillo, Edgardo
    ;
    Fabijanić, Matej
    ;
    Šumunec, Magdalena
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    Kapetanović, Nadir
    ;
    Michel, Andreas
    ;
    Groß, Wolfgang
    ;
    Weinmann, Martin
    The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-ideruification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.

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