Search Results for author:
Found 6 papers, 1 papers with code
ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets
Due to its conceptual simplicity and generality, compressive neural representation has emerged as a promising alternative to traditional compression methods for managing massive volumetric datasets.
Robust consensus control of second-order uncertain multiagent systems with velocity and input constraints (extended version)
In this paper, we investigate the consensus problem of second-order multiagent systems under directed graphs.
ConvFormer: Combining CNN and Transformer for Medical Image Segmentation
(2) A residual-shaped hybrid stem based on a combination of convolutions and Enhanced DeTrans is developed to capture both local and global representations to enhance representation ability.
DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization
Since 2016, we have witnessed the tremendous growth of artificial intelligence+visualization (AI+VIS) research.
Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation
Unlike the current literature on task-specific self-supervised pretraining followed by supervised fine-tuning, we utilize SSL to learn task-agnostic knowledge from heterogeneous data for various medical image segmentation tasks.
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation
In this paper, we propose a new ensemble learning framework for 3D biomedical image segmentation that combines the merits of 2D and 3D models.
Ranked #1 on
Cardiovascular MR Segmentaiton
on HVSMR 2016
