Search Results for author:
Found 5 papers, 2 papers with code
Kernel Attention Transformer (KAT) for Histopathology Whole Slide Image Classification
Transformer has been widely used in histopathology whole slide image (WSI) classification for the purpose of tumor grading, prognosis analysis, etc.
Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images Analysis
In this paper, we proposed a novel contrastive representation learning framework named Lesion-Aware Contrastive Learning (LACL) for histopathology whole slide image analysis.
Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions
While, it is challenging and yet significant in clinical applications to retrieve diagnostically relevant regions from a database that consists of histopathological whole slide images (WSIs) for a query ROI.
Deep Attributes from Context-Aware Regional Neural Codes
Results show that deep attribute approaches achieve state-of-the-art results, and outperforms existing peer methods with a significant margin, even though some benchmarks have little overlap of concepts with the pre-trained CNN models.
Factorization of View-Object Manifolds for Joint Object Recognition and Pose Estimation
Due to large variations in shape, appearance, and viewing conditions, object recognition is a key precursory challenge in the fields of object manipulation and robotic/AI visual reasoning in general.
