42 Result(s)
within
Conference Paper
Yike Guo
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Chapter and Conference Paper
Causal Reasoning Methods in Medical Domain: A Review
Causal reasoning has been a key topic in medical domain with many applications, in which the core problem is to infer the causal effects of medical treatments with data mining. However, there are obstacles suc...
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Chapter and Conference Paper
Verifying Design Through Generative Visualization of Neural Activity
Current neuroscience-focused approaches for evaluating the effectiveness of a design do not use direct visualization of mental activity. Inspired by S. Palazzo’s team we proposed a framework with reconstructio...
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Chapter and Conference Paper
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation
In cardiac magnetic resonance (CMR) imaging, a 3D high-resolution segmentation of the heart is essential for detailed description of its anatomical structures. However, due to the limit of acquisition duration...
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Chapter and Conference Paper
Self-training for Brain Tumour Segmentation with Uncertainty Estimation and Biophysics-Guided Survival Prediction
Gliomas are among the most common types of malignant brain tumours in adults. Given the intrinsic heterogeneity of gliomas, the multi-parametric magnetic resonance imaging (mpMRI) is the most effective techniq...
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Chapter and Conference Paper
BU-Trace: A Permissionless Mobile System for Privacy-Preserving Intelligent Contact Tracing
The coronavirus disease 2019 (COVID-19) pandemic has caused an unprecedented health crisis for the global. Digital contact tracing, as a transmission intervention measure, has shown its effectiveness on pandem...
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Chapter and Conference Paper
HNECV: Heterogeneous Network Embedding via Cloud Model and Variational Inference
Deep learning has been successfully used in heterogeneous network embedding. Although it shows excellent performance on preserving the structure and semantic characteristics of network while a large scale of t...
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Chapter and Conference Paper
Suggestive Annotation of Brain Tumour Images with Gradient-Guided Sampling
Machine learning has been widely adopted for medical image analysis in recent years given its promising performance in image segmentation and classification tasks. As a data-driven science, the success of mach...
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Chapter and Conference Paper
Deep Generative Model-Based Quality Control for Cardiac MRI Segmentation
In recent years, convolutional neural networks have demonstrated promising performance in a variety of medical image segmentation tasks. However, when a trained segmentation model is deployed into the real cli...
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Chapter and Conference Paper
An Econophysical Analysis of the Blockchain Ecosystem
We propose a novel modelling approach for the cryptocurrency ecosystem. We model on-chain and off-chain interactions as econophysical systems and employ methods from physical sciences to conduct interpretation...
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Chapter and Conference Paper
Chinese Entity Synonym Extraction from the Web
Entity synonyms play an important role in natural language processing applications, such as query expansion and question answering. There are three main distribution characteristics in texts on the web: (1) ap...
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Chapter and Conference Paper
Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction
Gliomas are the most common malignant brain tumours with intrinsic heterogeneity. Accurate segmentation of gliomas and their sub-regions on multi-parametric magnetic resonance images (mpMRI) is of great clinic...
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Chapter and Conference Paper
Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction
In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety of classification and regressi...
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Chapter and Conference Paper
Transfer Learning from Partial Annotations for Whole Brain Segmentation
Brain MR image segmentation is a key task in neuroimaging studies. It is commonly conducted using standard computational tools, such as FSL, SPM, multi-atlas segmentation etc, which are often registration-bas...
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Chapter and Conference Paper
Conditional Image Synthesis Using Stacked Auxiliary Classifier Generative Adversarial Networks
Synthesizing photo-realistic images has been a long-standing challenge in image processing and could provide crucial approaches for dataset augmentation and balancing. Traditional methods have trouble in deali...
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Chapter and Conference Paper
UMDISW: A Universal Multi-Domain Intelligent Scientific Workflow Framework for the Whole Life Cycle of Scientific Data
Existing scientific data management systems rarely manage scientific data from a whole-life-cycle perspective, and the value-creating steps defined throughout the cycle constitute essentially a scientific work...
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Chapter and Conference Paper
Generative Creativity: Adversarial Learning for Bionic Design
Generative creativity in the context of visual data refers to the generation process of new and creative images by composing features of existing ones. In this work, we aim to achieve generative creativity by ...
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Chapter and Conference Paper
Improved Accuracy Stock Price Change Prediction Model Using Trading Volume
This research aims to model the relationship between the change in stock price and the volume. Linear regression has been applied to the model at daily and at minute time scales; then Random Forest and Lasso r...
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Chapter and Conference Paper
Multi-domain and Sub-role Oriented Software Architecture for Managing Scientific Big Data
The existing Scientific Data Management Systems (SDMSs) usually focus on a single domain and the interaction pattern of each subsystem is complex. What’s more, the heterogeneity and multi-source of Scientific ...
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Chapter and Conference Paper
The Deep Poincaré Map: A Novel Approach for Left Ventricle Segmentation
Precise segmentation of the left ventricle (LV) within cardiac MRI images is a prerequisite for the quantitative measurement of heart function. However, this task is challenging due to the limited availability...
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Chapter and Conference Paper
Attacking Strategy of Multiple Unmanned Surface Vehicles Based on DAMGWO Algorithm
Unmanned combat system has received more and more attention with the development of modern weapons and equipment in recent years, which results in the application of unmanned surface vehicles (USVs) in the mil...
