Trusted Extremely Precise Mapping and Prediction for Emergency Management

Informazioni relative al progetto

TEMA

ID dell’accordo di sovvenzione: 101093003

DOI

10.3030/101093003

Data della firma CE 18 Novembre 2022

Data di avvio 1 Dicembre 2022

Data di completamento 30 Novembre 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 11 340 223,75

Contributo UE

€ 11 340 223,50

Coordinato da

ARISTOTELIO PANEPISTIMIO THESSALONIKIS
Greece

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (6)

Report on TEMA platform design, data models and architecture

Report documenting the technical specifications, data models and architecture of the TEMA platform, based on T2.2

Report on TEMA requirements

Document detailing the TEMA use cases and user requirements, based on Task T2.1

Report on phenomenon prediction and information fusion

Document reporting initial research results of Tasks T4.1 and T4.3

Report on algorithms for precise Digital Twin construction

Document reporting preliminary research results of Task T5.1

First report on algorithms for extreme data analytics

Document reporting initial research results of Tasks T3.1, T3.2 and T3.3

First report on dissemination and communication activities, clustering, and standardization recommendations

Overview of dissemination activities carried out during the project and communication materials produced. It also includes a detailed report with the progress of collaboration and clustering activities. It reports results of T7.1 and T7.4.

Pubblicazioni

Peer reviewed articles (9)

Clustering-Based Joint Topic-Sentiment Modeling of Social Media Data: A Neural Networks Approach

Autori: David Hanny, Bernd Resch
Pubblicato in: Information, Numero 15, 2024, ISSN 0000-0000
Editore: MDPI
DOI: 10.3390/info15040200

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus

Autori: Hedström, Anna; Bommer, Philine; Wickstrøm, Kristoffer K.; Samek, Wojciech; Lapuschkin, Sebastian; Höhne, Marina M. -C.
Pubblicato in: Transactions on Machine Learning Research, 2023, ISSN 0000-0000
Editore: TMLR (electronically published)
DOI: 10.48550/arxiv.2302.07265

Drowning in the Information Flood: Machine-Learning-Based Relevance Classification of Flood-Related Tweets for Disaster Management

Autori: Eike Blomeier, Sebastian Schmidt, Bernd Resch
Pubblicato in: Information, Numero 15, 2024, ISSN 0000-0000
Editore: MDPI
DOI: 10.3390/info15030149

AudioMNIST: Exploring Explainable Artificial Intelligence for audio analysis on a simple benchmark

Autori: Sören Becker, Johanna Vielhaben, Marcel Ackermann, Klaus-Robert Müller, Sebastian Lapuschkin, Wojciech Samek
Pubblicato in: n/a, 2023, ISSN 0000-0000
Editore: n/a
DOI: 10.1016/j.jfranklin.2023.11.038

Explainable Ai for Time Series Via Virtual Inspection Layers

Autori: Johanna Vielhaben; Sebastian Lapuschkin; Grégoire Montavon; Wojciech Samek
Pubblicato in: arXiv, 2023, ISSN 0000-0000
Editore: Science Direct
DOI: 10.1016/j.patcog.2024.110309

Human-Centered Evaluation of XAI Methods

Autori: Dawoud, Karam; Samek, Wojciech; Eisert, Peter; Lapuschkin, Sebastian; Bosse, Sebastian
Pubblicato in: 2023 IEEE International Conference on Data Mining Workshops (ICDMW), 2023, ISSN 0000-0000
Editore: IEEE
DOI: 10.48550/arxiv.2310.07534

Privacy-Shielding Autonomous Systems For Natural Disaster Management (Ndm): Targeted Regulation Of The Use Of Autonomous Systems For Natural Disaster Management Goals Before The Materialization Of The Privacy Harm

Autori: Georgios Bouchagiar, Vasileios Mygdalis, Ioannis Pitas
Pubblicato in: European Public Law, Numero 29, 2023, ISSN 0000-0000
Editore: Kluwer Law
DOI: 10.54648/euro2023020

Detection and Estimation of Gas Sources With Arbitrary Locations Based on Poisson's Equation

Autori: Dmitriy Shutin; Thomas Wiedemann; Patrick Hinsen
Pubblicato in: IEEE Open Journal of Signal Processing, Numero 5, 2023, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/OJSP.2023.3344076

From Hope to Safety: Unlearning Biases of Deep Models via Gradient Penalization in Latent Space

Autori: Dreyer, Maximilian; Pahde, Frederik; Anders, Christopher J.; Samek, Wojciech; Lapuschkin, Sebastian
Pubblicato in: Proceedings of the AAAI Conference on Artificial Intelligence, 2024, 2024, ISSN 0000-0000
Editore: AAAI
DOI: 10.48550/arxiv.2308.09437

Conference proceedings (14)

When Robotics Meets Distributed Learning: the Federated Learning Robotic Network Framework

Autori: Roberto Marino, Lorenzo Carnevale and Massimo Villari
Pubblicato in: ISCC 2023, 2023, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/ISCC58397.2023.10218022

Multimodal Geo-Information Extraction From Social Media For Supporting Decision-Making In Disaster Management

Autori: David Hanny, Bernd Resch
Pubblicato in: AGILE: GIScience Series, Numero 5, 2024, ISSN 0000-0000
Editore: n/a
DOI: 10.5194/agile-giss-5-28-2024

Active Learning for Identifying Disaster-Related Tweets: A Comparison with Keyword Filtering and Generic Fine-Tuning

Autori: David Hanny, Sebastian Schmidt, Bernd Resch
Pubblicato in: Intelligent Systems Conference, 2024, ISSN 0000-0000
Editore: n/a

XAI-based Comparison of Input Representations for Audio Event Classification

Autori: Frommholz, Annika; Seipel, Fabian; Lapuschkin, Sebastian; Samek, Wojciech; Vielhaben, Johanna
Pubblicato in: ACM Digital Library, 2023, ISSN 0000-0000
Editore: ACM
DOI: 10.48550/arxiv.2304.14019

Make Federated Learning a Standard in Robotics by Using ROS2

Autori: Roberto Marino, Lorenzo Carnevale, Maria Fazio, and Massimo Villari
Pubblicato in: BDCAT 2023, 2023, ISSN 0000-0000
Editore: ACM
DOI: 10.1145/3632366.3632373

PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits

Autori: Maximilian Dreyer, Erblina Purelku, Johanna Vielhaben, Wojciech Samek, Sebastian Lapuschkin
Pubblicato in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR), 2023, ISSN 0000-0000
Editore: IEEE
DOI: 10.48550/arXiv.2404.06453

Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations

Autori: Dreyer, Maximilian; Achtibat, Reduan; Samek, Wojciech; Lapuschkin, Sebastian
Pubblicato in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, 2023, ISSN 0000-0000
Editore: IEEE
DOI: 10.48550/arxiv.2311.16681

Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression

Autori: Dilyara Bareeva, Maximilian Dreyer, Frederik Pahde, Wojciech Samek, Sebastian Lapuschkin
Pubblicato in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPR), 2024, ISSN 0000-0000
Editore: IEEE
DOI: 10.5281/zenodo.11545313

Evaluating Deep Neural Network-based Fire Detection for Natural Disaster Management

Autori: Matthaios D Tzimas, Christos Papaioannidis, Vasileios Mygdalis and Ioannis Pitas
Pubblicato in: Proceedings of the IEEE/ACM 10th International Conference on Big Data Computing, Applications and Technologies, 2024
Editore: Association for Computing Machinery
DOI: 10.1145/3632366.3632369

Data Operational Driven AI-based Architecture for Natural Disaster Management

Autori: Serena Sebbio, Lorenzo Carnevale, Daniel Balouek, Antonino Galletta, Manish Parashar, Massimo Villari
Pubblicato in: CCGrid Workshop 2024, 2024, ISSN 0000-0000
Editore: CCGrid

Federated Learning on Raspberry Pi 4: A Comprehensive Power Consumption Analysis

Autori: Serena Sebbio, Gabriele Morabito, Alessio Catalfamo, Lorenzo Carnevale, and Maria Fazio
Pubblicato in: UCC 2023, 2023, ISSN 0000-0000
Editore: ACM
DOI: 10.1145/3603166.3632545

Distributed Superresolution Gas Source Localization Based on Poisson Equation

Autori: Dmitriy Shutin; Thomas Wiedemann; Patrick Hinsen
Pubblicato in: In proceedings of IEEE 9th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2023
Editore: IEEE
DOI: 10.1109/CAMSAP58249.2023.10403503

EDGEmergency: A Cloud-Edge Platform to Enable Pervasive Computing for Disaster Management

Autori: Mario Colosi, Marco Garofalo, Lorenzo Carnevale, Roberto Marino, Maria Fazio, and Massimo Villari
Pubblicato in: BDCAT 2023, 2023, ISSN 0000-0000
Editore: ACM
DOI: 10.1145/3632366.3632372

Supporting the Natural Disaster Management Distributing Federated Intelligence over the Cloud-Edge Continuum: the TEMA Architecture

Autori: Lorenzo Carnevale, Antonio Filograna, Francesco Arigliano, Roberto Marino, Armando Ruggeri, and Maria Fazio
Pubblicato in: BDCAT 2023, 2023
Editore: ACM
DOI: 10.1145/3632366.3632371

Other (5)

A Fresh Look at Sanity Checks for Saliency Maps

Autori: Anna Hedström, Leander Weber, Sebastian Lapuschkin, Marina Höhne
Pubblicato in: 2024, ISSN 0000-0000
Editore: n/a
DOI: 10.5281/zenodo.11546698

DualView: Data Attribution from the Dual Perspective

Autori: Galip Ümit Yolcu, Thomas Wiegand, Wojciech Samek, Sebastian Lapuschkin
Pubblicato in: n/a, 2024, ISSN 0000-0000
Editore: n/a
DOI: 10.48550/arXiv.2402.12118

Explaining Predictive Uncertainty by Exposing Second-Order Effects

Autori: Bley, Florian; Lapuschkin, Sebastian; Samek, Wojciech; Montavon, Grégoire
Pubblicato in: n/a, 2024, ISSN 0000-0000
Editore: n/a
DOI: 10.48550/arxiv.2401.17441

Layer-wise Feedback Propagation

Autori: Weber, Leander; Berend, Jim; Binder, Alexander; Wiegand, Thomas; Samek, Wojciech; Lapuschkin, Sebastian
Pubblicato in: n/a, 2023, ISSN 0000-0000
Editore: n/a
DOI: 10.48550/arxiv.2308.12053

FedROS: The ROS Framework for Federated Learning on Mobile Edge Devices

Autori: Lorenzo Carnevale, Mark Adrian Gambito, Roberto Marino, Davide Saraniti, Alessio Catalfamo, Massimo Villari
Pubblicato in: Flower AI Summit 2024, 2024, ISSN 0000-0000
Editore: n/a