4 papers · 1 filter
Energy-Efficient Plant Monitoring via Knowledge Distillation
Ilyass Moummad, Reda Bensaid, Kawtar Zaher +5
Recent advances in large-scale visual representation learning have significantly improved performance in plant species and plant disease recognition tasks. However, state-of-the-ar…
SLAD : Shared LoRA Adapters for Task Specific Distillation
Reda Bensaid, Yassir Bendou, Vincent Gripon +1
In the context of resource-constrained environments such as embedded systems, adapting reduced-size foundation models to downstream tasks has become increasingly popular. This has…
Efficient Few-Shot Learning for Edge AI via Knowledge Distillation on MobileViT
Shuhei Tsuyuki, Reda Bensaid, Jérémy Morlier +4
Efficient and adaptable deep learning models are an important area of deep learning research, driven by the need for highly efficient models on edge devices. Few-shot learning enab…
A Novel Benchmark for Few-Shot Semantic Segmentation in the Era of Foundation Models
Reda Bensaid, Vincent Gripon, François Leduc-Primeau +3
Few-shot semantic segmentation (FSS) is a crucial challenge in computer vision, driving extensive research into a diverse range of methods, from advanced meta-learning techniques t…