Transductive meta‑learning with enhanced feature ensemble for few‑shot semantic segmentation

The paper "Transductive Meta-Learning with Enhanced Feature Ensemble for Few-shot Semantic Segmentation" by Amin Karimi and Charalambos Poullis has been accepted for publication in Scientific Reports. TL;DR: We propose two-pass end-to-end method for few-shot semantic segmentation. The approach leverages an ensemble of visual features learned from pretrained classification Bcls

1 min read

More issues

TransGlow: Attention-augmented Transduction model based on Graph Neural Networks for Water Flow Forecasting

The paper "TransGlow: Attention-augmented Transduction model based on Graph Neural Networks for Water Flow Forecasting" by Naghmeh Shafiee Roudbari, Charalambos Poullis, Zachary Patterson, and Ursula Eicker, has been accepted for publication in the International Conference on Machine Learning and Applications (ICMLA), 2023. TL;DR: The hydrometric prediction of water quantity
1 min read

Analysis of error rate in hierarchical menu selection in immersive augmented reality

Our paper Analysis of error rate in hierarchical menu selection in immersive augmented reality has been accepted for publication in SPIE AR|VR|MR. The work is co-authored by Majid Pourmemar and Charalambos Poullis. The paper is now available: https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12449/124491L/Analysis-of-error-rate-in-hierarchical-menu-selection-in-immersive/10.1117/12.
1 min read