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CORDIS - Risultati della ricerca dell’UE
CORDIS

Powder is the only app offering a complete turnkey solution to automatically detect the best gaming moments, earn rewards from quests and challenges, and compete with other gamers.

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

Models creation and integration for new games (si apre in una nuova finestra)

By adding new games to our pipeline we are able to offer richer quests and challenges experiences

Challenge feed recommendation system (si apre in una nuova finestra)

Our existing RecSys project is reconverted and improved to support quests and challenges engagement

Wallet supports the 3 major blockchains (si apre in una nuova finestra)

Continuous effort of adding multiple blockchains / wallets supported

PC configurations management (si apre in una nuova finestra)

PC configurations management (continuous)

Integration of 30 detection models on PC (si apre in una nuova finestra)

PC app supports 30 detection models

Integration of 20 detection models on PC (si apre in una nuova finestra)

Integration of 20 AI detection models to our PC app

Onboarding discovery (si apre in una nuova finestra)

The user experience of quests and challenges is optimised on mobile

Setting up a process for prototype testing (si apre in una nuova finestra)

Industrialising our prototype testing

Continuous improvements on PC video recorder CPU & GPU usage (si apre in una nuova finestra)

Reduce CPU GPU usage on the users devices

Production launch and nominal operation on PC (si apre in una nuova finestra)

Crypto wallet is launched on our PC app at nominal operations

Digital assets marketplace test release (si apre in una nuova finestra)

In-app test release

Partners due diligence and selection (Crypto wallet) (si apre in una nuova finestra)

We identify audit and select one or multiple crypto wallet partners

Leaderboard launch (si apre in una nuova finestra)

A leaderboard where users can see their ranking compared to other participants to quests and challenges is relased

Integration of 15 detection models on PC (si apre in una nuova finestra)

PC app supports 15 detection models

Security and implementation testing (si apre in una nuova finestra)

Security is critical when handling users assets

Reaching 80% fidelity in new models detection (si apre in una nuova finestra)

Reaching high levels of fidelity in the new games added to the model

Improvement on the delays to create an integrate new models for new games (si apre in una nuova finestra)

In the perspective of scaling our user base, scaling our approach becomes critical

Optimisation of video resolution (si apre in una nuova finestra)

Optimisation of video resolution for external sharing

Redesign of the user profile to highlight rewards PC (si apre in una nuova finestra)

Redesign of the user profile to highlight rewards user library

Guaranteeing efficient R&D activities (si apre in una nuova finestra)

Ensuring an high level view of all R&D activities all along the project timeline

Redesign of the user profile to highlight rewards Mobile (si apre in una nuova finestra)

The user profile is redesigned fully to offer a consistent and enjoyable app experience

Reduce crash rate (si apre in una nuova finestra)

reduce the crash rate to 5 to offer a seamless experience

Digital assets marketplace product release (si apre in una nuova finestra)

Product release in the public app

Set up of automatic bots to share clips, achievements, etc. with other users (si apre in una nuova finestra)

Distribution set up of automatic bots to share clips achievements etc with other users

PhD research thesis (si apre in una nuova finestra)

"PhD research thesis ""Analysis of human behavior from video games using deep learning approaches"" (due in 36 months)"

Reach 100k Discord users (si apre in una nuova finestra)

Reach 100k Discord users on Powder servers / using the Powder discord bot

Pubblicazioni

Pattern Recognition Letters (si apre in una nuova finestra)

Autori: Liam Schoneveld, Alice Othmani, Hazem Abdelkawy
Pubblicato in: Pattern Recognition Letters, 2021, ISSN 0167-8655
Editore: Elsevier
DOI: 10.1016/j.patrec.2021.03.007

Comparing Learning Methodologies for Self-Supervised Audio-Visual Representation Learning (si apre in una nuova finestra)

Autori: H. Terbouche, L. Schoneveld, O. Benson, A. Othmani
Pubblicato in: IEEE Access, Numero Volume 10, pp. 41622-41638, 2022, ISSN 2169-3536
Editore: IEEE Access
DOI: 10.1109/ACCESS.2022.3164745

Towards a General Deep Feature Extractor for Facial Expression Recognition (si apre in una nuova finestra)

Autori: L. Schoneveld, A. Othmani
Pubblicato in: 2021 IEEE International Conference on Image Processing (ICIP), Numero 2339-2342, 2021, ISSN 2381-8549
Editore: IEEE Computer Society
DOI: 10.1109/ICIP42928.2021.9506025

Multi-Annotation Attention Model for Video Summarization

Autori: Hacene Terbouche, Maryan Morel, Mariano Rodriguez, Alice Othmani
Pubblicato in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, ISSN 3142-3151
Editore: IEEE/CVF (Computer Vision Foundation)

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