38 citations · 55 across the 7 of their papers we have counts for
7 papers
Integrated lithium niobate microwave photonic processing engine
Hanke Feng, Tong Ge, Xiaoqing Guo +9
Integrated microwave photonics is an intriguing field that leverages integrated photonic technologies for the generation, transmission, and manipulation of microwave signals in chi…
Joint Class-Affinity Loss Correction for Robust Medical Image Segmentation with Noisy Labels
Xiaoqing Guo, Yixuan Yuan
Noisy labels collected with limited annotation cost prevent medical image segmentation algorithms from learning precise semantic correlations. Previous segmentation arts of learnin…
A thermoelectric generation system using waste heat recovery from petrochemical pipeline to power wireless sensor
Bo Li, Xiao-Liang Guo, Yu-Tao Li
Wireless monitoring sensor gradually replaces wired equipment for data support in petrochemical industry production. And wireless monitoring sensor with continuous energy supply is…
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation
Xiaoqing Guo, Chen Yang, Baopu Li +1
Unsupervised domain adaptation (UDA) aims to transfer the knowledge from the labeled source domain to the unlabeled target domain. Existing self-training based UDA approaches assig…
Complementary Network with Adaptive Receptive Fields for Melanoma Segmentation
Xiaoqing Guo, Zhen Chen, Yixuan Yuan
Automatic melanoma segmentation in dermoscopic images is essential in computer-aided diagnosis of skin cancer. Existing methods may suffer from the hole and shrink problems with li…
Domain Knowledge Based Brain Tumor Segmentation and Overall Survival Prediction
Xiaoqing Guo, Chen Yang, Pak Lun Lam +2
Automatically segmenting sub-regions of gliomas (necrosis, edema and enhancing tumor) and accurately predicting overall survival (OS) time from multimodal MRI sequences have import…
Unsupervised End-to-end Learning for Deformable Medical Image Registration
Siyuan Shan, Wen Yan, Xiaoqing Guo +3
We propose a registration algorithm for 2D CT/MRI medical images with a new unsupervised end-to-end strategy using convolutional neural networks. The contributions of our algorithm…