41 citations · 107 across the 25 of their papers we have counts for
28 papers
Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection
Matteo Cardoni, Sam Leroux
Predictive Coding (PC) is a neural learning paradigm that enables parallelizable neural network layer updates. However, the main bottleneck of PC Networks (PCN) is the sequential b…
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…