Project description
Pioneering underwater scene sensing and analysis
Several underwater activities rely on reliable and elaborated underwater scene sensing and analysis. Consequently, there is a rising interest in visual-based underwater sensing. However, deep learning methods exploration in this field is limited. On the other hand, sensing modalities based on single-photon cameras (SPCs) and transient imaging are gradually maturing to allow sensing in challenging visibility conditions. The EU-funded iSEAu project will proceed with the higher advancement of underwater scene sensing. The project will combine the respective advantages of SPCs, multispectral and conventional cameras and invest in intensive knowledge transfer to connect computer vision, machine learning and remote sensing to optimally confront the underwater visual sensing challenges.
Objective
Reliable and detailed underwater scene sensing, and analysis has a fundamental role in numerous underwater activities drawing both scientific and economic interest. Computer vision and remote sensing have evolved impressively in the last decade, propelled also by advancements in deep learning, enabling unprecedented levels of robust and automatic information extraction from visual data. At the same time, there is increasing interest in visual based underwater sensing, however, deep learning methods are less explored in this domain. On the other hand, sensing modalities based on Single Photon Cameras (SPCs) and transient imaging are gradually maturing, having certain characteristics that allow sensing in challenging visibility conditions, as the ones of underwater environments.
iSEAu aims to significantly advance the state-of-the-art of underwater scene sensing by bridging the gap in the use of data-driven methods in underwater perception, and by combining the respective advantages of SPCs, multispectral and conventional cameras. Investing on intensive knowledge transfer, the goal is to bring together the fields of computer vision, machine learning and remote sensing for optimally addressing the underwater visual sensing challenges. The project objectives address these challenges in two levels. The first concerns the development of methods for removing the water from underwater images by harnessing the power of learning-based methods, and the development of methods based on SPC transient imaging for perception in challenging visibility conditions. The second level concerns the adaptation and enhancement to the underwater domain of state-of-the-art methods for image-based extraction of structural and semantic information, and their field-testing considering representative application scenarios. In summary, iSEAu will provide novel data-driven methodologies and technological solutions to researchers, scientists and users for underwater sensing of unmatched fidelity.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors optical sensors
- natural sciences physical sciences theoretical physics particle physics photons
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2020
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
157 72 ATHINA
Greece
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.