An analysis model of diagnosis and treatment for COVID-19 pandemic based on medical information fusion [0.03%]
基于医疗信息融合的新冠肺炎诊治分析模型研究
Fang Hu,Mingfang Huang,Jing Sun et al.
Fang Hu et al.
Exploring the complicated relationships underlying the clinical information is essential for the diagnosis and treatment of the Coronavirus Disease 2019 (COVID-19). Currently, few approaches are mature enough to show operational impact. Bas...
DiCyc: GAN-based deformation invariant cross-domain information fusion for medical image synthesis [0.03%]
基于生成对抗网络的变形不变跨域信息融合医学图像合成方法 DiCyc
Chengjia Wang,Guang Yang,Giorgos Papanastasiou et al.
Chengjia Wang et al.
Cycle-consistent generative adversarial network (CycleGAN) has been widely used for cross-domain medical image synthesis tasks particularly due to its ability to deal with unpaired data. However, most CycleGAN-based synthesis methods cannot...
COVID-19 and Non-COVID-19 Classification using Multi-layers Fusion From Lung Ultrasound Images [0.03%]
基于肺部超声图像多层次融合的COVID-19与非COVID-19分类方法
Ghulam Muhammad,M Shamim Hossain
Ghulam Muhammad
COVID-19 or related viral pandemics should be detected and managed without hesitation, since the virus spreads very rapidly. Often with insufficient human and electronic resources, patients need to be checked from stable patients using vita...
COVID-19 classification by CCSHNet with deep fusion using transfer learning and discriminant correlation analysis [0.03%]
基于迁移学习和判别相关分析的深层融合新型冠状病毒分类的CCSHNet网络
Shui-Hua Wang,Deepak Ranjan Nayak,David S Guttery et al.
Shui-Hua Wang et al.
Aim: : COVID-19 is a disease caused by a new strain of coronavirus. Up to 18th October 2020, worldwide there have been 39.6 million confirmed cases resulting in more than 1.1 million deaths. To improve diagnosis, we aimed...
Covid-19 classification by FGCNet with deep feature fusion from graph convolutional network and convolutional neural network [0.03%]
图卷积网络和卷积神经网络的深度特征融合的FGCNet对COVID-19进行分类
Shui-Hua Wang,Vishnu Varthanan Govindaraj,Juan Manuel Górriz et al.
Shui-Hua Wang et al.
(Aim) COVID-19 is an infectious disease spreading to the world this year. In this study, we plan to develop an artificial intelligence based tool to diagnose on chest CT images. (Method) On one hand, we extract features from a self-created ...
Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions [0.03%]
股票市场预测中的融合技术：关于必要性、最新发展和未来潜在方向的十年回顾
Ankit Thakkar,Kinjal Chaudhari
Ankit Thakkar
Investment in a financial market is aimed at getting higher benefits; this complex market is influenced by a large number of events wherein the prediction of future market dynamics is challenging. The investors' etiquettes towards stock mar...
Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects [0.03%]
通过深度学习重新审视人群行为分析：分类、异常检测、人群情绪、数据集、机遇和前景
Francisco Luque Sánchez,Isabelle Hupont,Siham Tabik et al.
Francisco Luque Sánchez et al.
Crowd behaviour analysis is an emerging research area. Due to its novelty, a proper taxonomy to organise its different sub-tasks is still missing. This paper proposes a taxonomic organisation of existing works following a pipeline, where su...
The introduction of population migration to SEIAR for COVID-19 epidemic modeling with an efficient intervention strategy [0.03%]
人口迁移对COVID-19疫情SEIAR模型的影响及高效干预策略
Min Chen,Miao Li,Yixue Hao et al.
Min Chen et al.
In this paper, we present a mathematical model of an infectious disease according to the characteristics of the COVID-19 pandemic. The proposed enhanced model, which will be referred to as the SEIR (Susceptible-Exposed-Infectious-Recovered)...
Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation [0.03%]
神经影像中多模式数据融合的进展：概述，挑战和新方向
Yu-Dong Zhang,Zhengchao Dong,Shui-Hua Wang et al.
Yu-Dong Zhang et al.
Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, cor...
Gema Bello-Orgaz,Jason J Jung,David Camacho
Gema Bello-Orgaz
Big data has become an important issue for a large number of research areas such as data mining, machine learning, computational intelligence, information fusion, the semantic Web, and social networks. The rise of different big data framewo...