1 citations · 1 across the 6 of their papers we have counts for
6 papers
Layer-wise Noise Guided Selective Wavelet Reconstruction for Robust Medical Image Segmentation
Yuting Lu, Ziliang Wang, Weixin Xu +4
Clinical deployment requires segmentation models to stay stable under distribution shifts and perturbations. The mainstream solution is adversarial training (AT) to improve robustn…
CARE: Anti-entanglement Ultrasound Image Segmentation via Channel-Aware Region Extrication
Weixin Xu, Yuting Lu, Luqi Gong +3
Accurate ultrasound image segmentation is fundamentally challenged by target-context entanglement, where lesion cues are easily mixed with surrounding tissues and artifacts of simi…
PneumoLLM: Harnessing the Power of Large Language Model for Pneumoconiosis Diagnosis
Meiyue Song, Zhihua Yu, Jiaxin Wang +11
The conventional pretraining-and-finetuning paradigm, while effective for common diseases with ample data, faces challenges in diagnosing data-scarce occupational diseases like pne…
Multi-granularity Backprojection Transformer for Remote Sensing Image Super-Resolution
Jinglei Hao, Wukai Li, Binglu Wang +4
Backprojection networks have achieved promising super-resolution performance for nature images but not well be explored in the remote sensing image super-resolution (RSISR) field d…
Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network for Remote Sensing Image Super-Resolution
Yuting Lu, Lingtong Min, Binglu Wang +4
Remote sensing image super-resolution (RSISR) plays a vital role in enhancing spatial detials and improving the quality of satellite imagery. Recently, Transformer-based models hav…
Stochastic Neural Networks with Infinite Width are Deterministic
Liu Ziyin, Hanlin Zhang, Xiangming Meng +3
This work theoretically studies stochastic neural networks, a main type of neural network in use. We prove that as the width of an optimized stochastic neural network tends to infi…