4 papers
Holonic Active Distillation for Scalable Multi-Agent Learning in Multi-Sensor Systems
Dani Manjah, Tim Bary, Benoît Macq +1
The rapid expansion of sensor-based networks introduces major challenges in scalability, adaptability, and knowledge transfer, especially in open environments where new subsystems…
Data-Efficient Stream-Based Active Distillation for Scalable Edge Model Deployment
Dani Manjah, Tim Bary, Benoît Gérin +2
Edge camera-based systems are continuously expanding, facing ever-evolving environments that require regular model updates. In practice, complex teacher models are run on a central…
Patient-specific vs Multi-Patient Vision Transformer for Markerless Tumor Motion Forecasting
Gauthier Rotsart de Hertaing, Dani Manjah, Benoit Macq
Background: Accurate forecasting of lung tumor motion is essential for precise dose delivery in proton therapy. While current markerless methods mostly rely on deep learning, trans…
Camera clustering for scalable stream-based active distillation
Dani Manjah, Davide Cacciarelli, Christophe De Vleeschouwer +1
We present a scalable framework designed to craft efficient lightweight models for video object detection utilizing self-training and knowledge distillation techniques. We scrutini…