10 papers
Le MuMo JEPA: Multi-Modal Self-Supervised Representation Learning with Learnable Fusion Tokens
Ciem Cornelissen, Sam Leroux, Pieter Simoens
Self-supervised learning has emerged as a powerful paradigm for learning visual representations without manual annotations, yet most methods still operate on a single modality and…
THDC: Training Hyperdimensional Computing Models with Backpropagation
Hanne Dejonghe, Sam Leroux
Hyperdimensional computing (HDC) offers lightweight learning for energy-constrained devices by encoding data into high-dimensional vectors. However, its reliance on ultra-high dime…
Efficient On-Board Processing of Oblique UAV Video for Rapid Flood Extent Mapping
Vishisht Sharma, Sam Leroux, Lisa Landuyt +2
Effective disaster response relies on rapid disaster response, where oblique aerial video is the primary modality for initial scouting due to its ability to maximize spatial covera…
Privacy-Preserving Computer Vision for Industry: Three Case Studies in Human-Centric Manufacturing
Sander De Coninck, Emilio Gamba, Bart Van Doninck +3
The adoption of AI-powered computer vision in industry is often constrained by the need to balance operational utility with worker privacy. Building on our previously proposed priv…
In-Field Mapping of Grape Yield and Quality with Illumination-Invariant Deep Learning
Ciem Cornelissen, Sander De Coninck, Axel Willekens +2
This paper presents an end-to-end, IoT-enabled robotic system for the non-destructive, real-time, and spatially-resolved mapping of grape yield and quality (Brix, Acidity) in viney…
Predictive Coding-based Deep Neural Network Fine-tuning for Computationally Efficient Domain Adaptation
Matteo Cardoni, Sam Leroux
As deep neural networks are increasingly deployed in dynamic, real-world environments, relying on a single static model is often insufficient. Changes in input data distributions c…