2 citations · 10 across the 39 of their papers we have counts for
7 papers · 1 filter
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks
Lehan Wang, Haonan Wang, Honglong Yang +4
Several medical Multimodal Large Languange Models (MLLMs) have been developed to address tasks involving visual images with textual instructions across various medical modalities,…
GTPT: Group-based Token Pruning Transformer for Efficient Human Pose Estimation
Haonan Wang, Jie Liu, Jie Tang +4
In recent years, 2D human pose estimation has made significant progress on public benchmarks. However, many of these approaches face challenges of less applicability in the industr…
S&D Messenger: Exchanging Semantic and Domain Knowledge for Generic Semi-Supervised Medical Image Segmentation
Qixiang Zhang, Haonan Wang, Xiaomeng Li
Semi-supervised medical image segmentation (SSMIS) has emerged as a promising solution to tackle the challenges of time-consuming manual labeling in the medical field. However, in…
ADLDA: A Method to Reduce the Harm of Data Distribution Shift in Data Augmentation
Haonan Wang
This study introduces a novel data augmentation technique, ADLDA, aimed at mitigating the negative impact of data distribution shifts caused by the data augmentation process in com…
Research on geometric figure classification algorithm based on Deep Learning
Ruiyang Wang, Haonan Wang, Junfeng Sun +2
In recent years, with the rapid development of computer information technology, the development of artificial intelligence has been accelerating. The traditional geometry recogniti…
Towards Better Text-to-Image Generation Alignment via Attention Modulation
Yihang Wu, Xiao Cao, Kaixin Li +4
In text-to-image generation tasks, the advancements of diffusion models have facilitated the fidelity of generated results. However, these models encounter challenges when processi…