Anatomical labeling of intracranial arteries with deep learning in patients with cerebrovascular disease

A Hilbert, J Rieger, VI Madai, EM Akay… - Frontiers in …, 2022 - frontiersin.org
Brain arteries are routinely imaged in the clinical setting by various modalities, eg, time-of-
flight magnetic resonance angiography (TOF-MRA). These imaging techniques have great …

Advances in the development of representation learning and its innovations against COVID-19

P Li, MM Parvej, C Zhang, S Guo, J Zhang - COVID, 2023 - mdpi.com
In bioinformatics research, traditional machine-learning methods have demonstrated
efficacy in addressing Euclidean data. However, real-world data often encompass non …

Node and edge dual-masked self-supervised graph representation

P Tang, C Xie, H Duan - Knowledge and Information Systems, 2024 - Springer
Self-supervised graph representation learning has been widely used in many intelligent
applications since labeled information can hardly be found in these data environments …

Surface Defect Detection Based on ResNet Classification Network with GAN Optimized

H Fu, Z Zhou, Z Zeng, T Sang, Y Zhu… - 2022 IEEE Smartworld …, 2022 - ieeexplore.ieee.org
Surface defect detection plays an important role in industrial domains. The defect failed to
report and the defect missed to report will have a serious impact on the whole industrial …