A data aggregation based approach to exploit dynamic spatio-temporal correlations for citywide crowd flows prediction in fog computing

A Ali, Y Zhu, M Zakarya - Multimedia Tools and Applications, 2021 - Springer
Accurate and timely predicting citywide traffic crowd flows precisely is crucial for public
safety and traffic management in smart cities. Nevertheless, its crucial challenge lies in how …

Citywide traffic flow prediction based on multiple gated spatio-temporal convolutional neural networks

C Chen, K Li, SG Teo, X Zou, K Li, Z Zeng - ACM Transactions on …, 2020 - dl.acm.org
Traffic flow prediction is crucial for public safety and traffic management, and remains a big
challenge because of many complicated factors, eg, multiple spatio-temporal dependencies …

Multi-scale attention network for diabetic retinopathy classification

MT Al-Antary, Y Arafa - IEEE Access, 2021 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is a highly prevalent complication of diabetes mellitus, which
causes lesions on the retina that affect vision which may lead to blindness if it is not detected …

LE-UDA: Label-efficient unsupervised domain adaptation for medical image segmentation

Z Zhao, F Zhou, K Xu, Z Zeng, C Guan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
While deep learning methods hitherto have achieved considerable success in medical
image segmentation, they are still hampered by two limitations:(i) reliance on large-scale …

A review of nuclei detection and segmentation on microscopy images using deep learning with applications to unbiased stereology counting

SS Alahmari, D Goldgof, LO Hall… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The detection and segmentation of stained cells and nuclei are essential prerequisites for
subsequent quantitative research for many diseases. Recently, deep learning has shown …

Dsal: Deeply supervised active learning from strong and weak labelers for biomedical image segmentation

Z Zhao, Z Zeng, K Xu, C Chen… - IEEE journal of …, 2021 - ieeexplore.ieee.org
Image segmentation is one of the most essential biomedical image processing problems for
different imaging modalities, including microscopy and X-ray in the Internet-of-Medical …

A hierarchical deep convolutional neural network and gated recurrent unit framework for structural damage detection

J Yang, L Zhang, C Chen, Y Li, R Li, G Wang… - Information …, 2020 - Elsevier
Structural damage detection has become an interdisciplinary area of interest for various
engineering fields, while the available damage detection methods are being in the process …

Texture attention network for diabetic retinopathy classification

MD Alahmadi - IEEE Access, 2022 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) is a disease caused by a high level of glucose in retina vessels.
This malicious disease put millions of people around the world at risk for vision loss each …

Mt-uda: Towards unsupervised cross-modality medical image segmentation with limited source labels

Z Zhao, K Xu, S Li, Z Zeng, C Guan - … –October 1, 2021, Proceedings, Part I …, 2021 - Springer
The success of deep convolutional neural networks (DCNNs) benefits from high volumes of
annotated data. However, annotating medical images is laborious, expensive, and requires …

Meta-hallucinator: Towards few-shot cross-modality cardiac image segmentation

Z Zhao, F Zhou, Z Zeng, C Guan, SK Zhou - International Conference on …, 2022 - Springer
Abstract Domain shift and label scarcity heavily limit deep learning applications to various
medical image analysis tasks. Unsupervised domain adaptation (UDA) techniques have …