Remix Science: The Sound of Data – Science meets Music

Project description: The Sound of Data explores new ways of creating, performing, and experiencing music and art by using multi source data as the building blocks in the creative process, i.e. remixing the scientific and artistic approaches herein. It is centered around the idea to use datasets obtained in different contexts as a core determinant … Continued

SmartSchoul2025: The future Luxembourg School

Project description: SnT has partnered with the Ministry of National Education represented by its department for the Coordination of Educational and Technological Research and Innovation SCRIPT and the Lycée Edward Steichen à Clervaux (LESC) in defining the Smart Schoul 2025 project. The goal of this project is to create a fertile environment for pupils to be … Continued

DETECT: Towards edge-optimized deep learning for explainable quality control

Project description: The current evolution of the manufacturing domain towards the so-called Industry 4.0 demands for more flexible solutions. Deep Neural Networks (DNNs) provide this by automatically learning high level features. However, its wide-spread application   in industry is mainly hampered by two factors: high hardware demands and lacking explainability of classification decisions.  Neural networks tend … Continued

Visual Quality Control in Manufacturing

Project description: The project objective is to investigate the usage of Deep Neural Networks (DNNs) for on-the-edge image analytics, i.e., product control in the industrial domain. The ever-growing throughput and quality demands of modern manufacturing make it impossible to rely on the human eye for a rising number of quality assessment procedures. This development leads … Continued

Proving Digital Asset Integrity Using Deepfake Detection  

Project description: In order to recover confidence in the growing digital ecosystem, especially in this new era of fake news and DeepFake, the goal of this project is to strengthen the confidence in the integrity of a digital asset  through its content (e.g., videos, photos, audio). The project will investigate the latest approaches for detecting … Continued

UNFAKE: Unsupervised multi-type explainable deepFAKE detection

Project description: Given the threat of deepfakes, significant efforts have been made for proposing deepfake detection methods.  Nevertheless, these methods remain not sufficiently mature for real-world deployment. as they usually specialize in detecting one type of deepfakes, which limits their generalization capability, and typically rely on very large models. Hence, UNFAKE aims to provide a more … Continued

FakeDeTer: DeepFake Detection using Spatio-Temporal-Spectral Representations for Effective Learning

Project description: With the fast advances in Artificial intelligence, deepfake videos are becoming more accessible and realistic-looking.  Their twisted use,  constitutes a threat to society  Existing deepfake detection methods mostly rely on exploiting discrepancies caused by a given generation method. The goal of FakeDeTeR is to define a more generic approach that captures even deepfakes … Continued

ID-form – Face Identification Under Deformations

Project description: Being constrained to keep a straight face should no longer be a condition for a well-performing face recognition system. IDform proposes to robustly identify people from their faces in full dynamic conditions. The idea is to build on the success of today’s best performing face systems that use deep learning; however, instead of … Continued

Deep Learning of 3D Scanned Data

Project description: The general idea of this project is to investigate recent advances of geometric deep learning to leverage raw 3D scans to higher level representations. One of the main goals  is to infer Computer-Aided Design (CAD) models directly from 3D scans. To that aim, multiple aspects are being considered such as 3D scan refinement … Continued

FREE-3D: Feature-based Reverse Engineering Of 3D Scans

Project description: Recently,  some efforts have been made for proposingAI algorithms that learn Computer-Aided Designs (CADs) of real objects. The idea of these methods is to scan objects using 3D scanners and conclude CAD procedures. However, current solutions either require the input of the designers or are limited to simple objects and are not compliant … Continued