activity
20162026
most citedDecoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video

2 citations · 7 across the 15 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

cs.CV2025

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…

cs.CV20251 cited

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…

cs.LG2025

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…

cs.CV20251 cited

Enabling Privacy-Aware AI-Based Ergonomic Analysis

Sander De Coninck, Emilio Gamba, Bart Van Doninck +3

Musculoskeletal disorders (MSDs) are a leading cause of injury and productivity loss in the manufacturing industry, incurring substantial economic costs. Ergonomic assessments can…

cs.CV20251 cited

Adaptive Clustering for Efficient Phenotype Segmentation of UAV Hyperspectral Data

Ciem Cornelissen, Sam Leroux, Pieter Simoens

Unmanned Aerial Vehicles (UAVs) combined with Hyperspectral imaging (HSI) offer potential for environmental and agricultural applications by capturing detailed spectral information…