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Article
Open AccessCybersecurity knowledge graphs construction and quality assessment
Cyber-attack activities are complex and ever-changing, posing severe challenges to cybersecurity personnel. Introducing knowledge graphs into the field of cybersecurity helps depict the intricate cybersecurity...
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Article
Fast Gradient Method for Low-Rank Matrix Estimation
Projected gradient descent and its Riemannian variant belong to a typical class of methods for low-rank matrix estimation. This paper proposes a new Nesterov’s Accelerated Riemannian Gradient algorithm using e...
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Article
Observer-based decentralized fuzzy control for connected nonlinear vehicle systems
This article analyzes the tracking control of a type of connected nonlinear vehicle system, where the problem of hacker attacks and external disturbance is considered. A decentralized fuzzy control method base...
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Article
Deep Learning-Based Quantum State Tomography With Imperfect Measurement
In recent years, neural network estimator-based quantum state tomography has gained its popularity. Inspired by advances in the field of state-of-the-art deep learning techniques, we apply the U-net model and ...
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Article
Open AccessSingle-cell RNA sequencing to track novel perspectives in HSC heterogeneity
As the importance of cell heterogeneity has begun to be emphasized, single-cell sequencing approaches are rapidly adopted to study cell heterogeneity and cellular evolutionary relationships of various cells, i...
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Chapter and Conference Paper
Computer-Aided Tuberculosis Diagnosis with Attribute Reasoning Assistance
Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to much time and resource consumpt...
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Article
Comparison of automated and manual DWI-ASPECTS in acute ischemic stroke: total and region-specific assessment
To compare the DWI-Alberta Stroke Program Early Computed Tomography Score calculated by a deep learning–based automatic software tool (eDWI-ASPECTS) with the neuroradiologists’ evaluation for the acute stroke,...
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Article
Open AccessA clinically applicable deep-learning model for detecting intracranial aneurysm in computed tomography angiography images
Intracranial aneurysm is a common life-threatening disease. Computed tomography angiography is recommended as the standard diagnosis tool; yet, interpretation can be time-consuming and challenging. We present ...
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Chapter and Conference Paper
Learning Hybrid Representations for Automatic 3D Vessel Centerline Extraction
Automatic blood vessel extraction from 3D medical images is crucial for vascular disease diagnoses. Existing methods based on convolutional neural networks (CNNs) may suffer from discontinuities of extracted v...
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Chapter and Conference Paper
Image Super-Resolution Reconstruction with Dense Residual Attention Module
Deep convolutional neural networks have recently achieved great success in the field of image super-resolution. However, most of the super-resolution methods based on deep neural network do not make full use o...
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Chapter and Conference Paper
Globally Guided Progressive Fusion Network for 3D Pancreas Segmentation
Recently 3D volumetric organ segmentation attracts much research interest in medical image analysis due to its significance in computer aided diagnosis. This paper aims to address the pancreas segmentation tas...
