20 citations · 40 across the 46 of their papers we have counts for
5 papers · 1 filter
Image Classification with Deep Reinforcement Active Learning
Mingyuan Jiu, Xuguang Song, Hichem Sahbi +5
Deep learning is currently reaching outstanding performances on different tasks, including image classification, especially when using large neural networks. The success of these m…
Multi-label Classification using Deep Multi-order Context-aware Kernel Networks
Mingyuan Jiu, Hailong Zhu, Hichem Sahbi
Multi-label classification is a challenging task in pattern recognition. Many deep learning methods have been proposed and largely enhanced classification performance. However, mos…
Learning Coarse-to-Fine Pruning of Graph Convolutional Networks for Skeleton-based Recognition
Hichem Sahbi
Magnitude Pruning is a staple lightweight network design method which seeks to remove connections with the smallest magnitude. This process is either achieved in a structured or un…
Designing Semi-Structured Pruning of Graph Convolutional Networks for Skeleton-based Recognition
Hichem Sahbi
Deep neural networks (DNNs) are nowadays witnessing a major success in solving many pattern recognition tasks including skeleton-based classification. The deployment of DNNs on edg…
Few-Shot Object Detection with Sparse Context Transformers
Jie Mei, Mingyuan Jiu, Hichem Sahbi +2
Few-shot detection is a major task in pattern recognition which seeks to localize objects using models trained with few labeled data. One of the mainstream few-shot methods is tran…