1 Key Laboratory of Intelligent Perception and Image Understanding of ... In this paper, we propose a novel multi-task representation learning architecture coupled with the task of supervised node ...

obtaining 22.0% and 6.2% higher accuracies on the face-detetction and object classification tasks respectively. These results demonstrate the effectiveness of multi-task training of deep learning ...

deep multiple instance learning (MIL) has become the main approach to classify histopatho-logical images with only slide-level annotation. However, three major challenges including lack of data ...

This repo contains the code for "Enhancing Multi-Task Learning for Image Segmentation using soft attention blocks ... MTL model with auxiliary tasks of Boundary box detection and Classification was ...

In the meanwhile, we propose a multi-task learning (MTL) scheme, which combines pixel-level segmentation and global image-level category classification. The proposed architecture is based on a fully ...