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CORDIS - EU research results
CORDIS

Deep-Learning for Multimodal Sensor Fusion

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

ML Concept (opens in new window)

Report on selection of baseline machine learning algorithms ANN topologies and concepts for modifications optimizations and algorithm training

Algorithm Testing & Validation Report (opens in new window)

Report on the methodology applied and results of testing and algorithm validation.

Training Data Generation Report (opens in new window)

Report on training data generation for the three use cases It includes description of data produced by the consortium either gathered in field campaigns or in simulation It is linked to the output of tasks T41 T42 and T43

Datasets for Public Dissemination (opens in new window)

Report and description of datasets prepared for public dissemination in the Public Data Repository in WP7.

Evaluation ML Approaches (opens in new window)

Report on indepth evaluation and selection of ML approaches available on basis of D23 and D24

Verification & Demonstration Concept (opens in new window)

Report on concept for algorithm field validations usecase demonstrations and final joint field demonstration

Field Validation Report (opens in new window)

Report and documentation of the field validations in Germany, Israel and Spain.

Algorithm Training & Optimization Results (opens in new window)

Report on the modified core ML algorithms and the results of preliminary training 2nd iteration with data collected in WP4

Training Data Concept (opens in new window)

Report on concepts for collection and generation of training data and algorithm testing taking into account D23

Sensor Concept (opens in new window)

Report on feasible sensor pairings and specifications based on results of D21

Use-Case Requirements (opens in new window)

Report describing the use cases and summarizing functional requirements for robotic systems for each use case

Final Demonstration Report (opens in new window)

Report and documentation of final joint demonstration.

Public Data Repository (opens in new window)

Public online repository for training data generated in DeeperSense, including metadata and documentation. PDR concept will be documented in D7.1.

Data Management Plan (opens in new window)

This deliverable will formalize a data management plan according to the requirements of the Open Research Data Pilot

Communication & Dissemination Material (opens in new window)

Website, social media channels, print material templates. Documentation of C&D Material will be included in D7.1.

Final DeeperSense Framework (opens in new window)

Updated version of D3.3, with updated software and documentation.

Draft DeeperSense Framework (opens in new window)

Preliminary version and documentation of software library with the (trained) core ML algorithms that will be applied to UC1, 2 and 3. Final version to be released as D5.3.

Publications

Sonar-to-RGB Image Translation for Diver Monitoring in Poor Visibility Environments (opens in new window)

Author(s): Bilal Wehbe; Nimish Shah; Miguel Bande; Christian Backe
Published in: Oceans 2022, 2022
Publisher: IEEE
DOI: 10.1109/oceans47191.2022.9977024

Spatial Acoustic Projection for 3D Imaging Sonar Reconstruction (opens in new window)

Author(s): Arnold, Sascha; Wehbe, Bilal
Published in: IEEE International Conference on Robotics and Automation (ICRA) 2022, 2022
Publisher: IEEE
DOI: 10.1109/icra46639.2022.9812277

Self-supervised Learning for Sonar Image Classification (opens in new window)

Author(s): Preciado-Grijalva, Alan; Wehbe, Bilal; Firvida, Miguel Bande; Valdenegro-Toro, Matias
Published in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, Page(s) 1499-1508
Publisher: IEEE
DOI: 10.1109/cvprw56347.2022.00156

Pre-trained Models for Sonar Images (opens in new window)

Author(s): Valdenegro-Toro, Matias; Preciado-Grijalva, Alan; Wehbe, Bilal
Published in: Global Oceans 2021, 2021
Publisher: arXiv
DOI: 10.23919/oceans44145.2021.9705825

Self-Supervised Monocular Depth Underwater (opens in new window)

Author(s): Amitai, Shlomi; Klein, Itzik; Treibitz, Tali
Published in: 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023, Page(s) 1098-1104
Publisher: IEEE
DOI: 10.1109/icra48891.2023.10161161

Creating Rich Metadata for Collaborative Research: Case Studies and Challenges (opens in new window)

Author(s): Backe, Christian; Gooran Orimi, Atefeh; Briken, Veit; Hamlaoui, Rayen; Görner, Hendrik
Published in: NFDI4Ing Conference 2023, Issue 1, 2023
Publisher: ZENODO
DOI: 10.5281/zenodo.8430752

Increasing diver safety for heavy underwater works by Sonar-to-Video Image Translation

Author(s): J Lorscheidt, B Wehbe, D Cesar, T Vögele, T Becker
Published in: ISCRAM 2023, 2023
Publisher: ISCRAM

Distortion Correction of AUV-acquired Side-Scan Sonar Data (opens in new window)

Author(s): V. Franchi, H. Rajani, R. Garcia, B. Martinez-Clavel and N. Gracias
Published in: OCEANS 2023 - Limerick, 2023, Page(s) 1-10
Publisher: IEEE
DOI: 10.1109/oceanslimerick52467.2023.10244553

Enhancing the underwater vision to increase the safety of heavy underwater works by Intersensory learning – a use case in the European DeeperSense research project

Author(s): Christian Illing, Tom Becker
Published in: Proceedings of MARESC 2021, 2021
Publisher: NN

FLSea: Underwater Visual-Inertial and Stereo-Vision Forward-Looking Datasets (opens in new window)

Author(s): Randall, Yelena; Treibitz, Tali
Published in: The International Journal of Robotics Research, Issue Doctoral Thesis, 2023
Publisher: University Haifa
DOI: 10.48550/arxiv.2302.12772

A convolutional vision transformer for semantic segmentation of side-scan sonar data (opens in new window)

Author(s): Hayat Rajani; Nuno Gracias; Rafael Garcia
Published in: Ocean Engineering, Issue 286, 2023, Page(s) 115647, ISSN 0029-8018
Publisher: Pergamon Press Ltd.
DOI: 10.1016/j.oceaneng.2023.115647

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