Browsing NTNU Open by Author "Wang, Hao"

Now showing items 41-60 of 148

    • Chronic Diseases and Health Monitoring Big Data: A Survey 

      Lin, Rongheng; Ye, Zezhou; Wang, Hao; Wu, Budan (Journal article; Peer reviewed, 2018)
      With the advancement of technology in data science and network technology, the world has stepped into the Era of Big Data, and the medical field is rich in data suitable for analysis. Thus, in recent years, there has been ...

    • A comparison of Generative Adversarial Networks for automated prostate cancer detection on T2-weighted MRI 

      Patsanis, Alexandros; Sunoqrot, Mohammed R. S.; Langørgen, Sverre; Wang, Hao; Selnæs, Kirsten Margrete; Bertilsson, Maria Helena; Bathen, Tone Frost; Elschot, Mattijs (Journal article; Peer reviewed, 2023)
      Generative Adversarial Networks (GANs) have shown potential in medical imaging. In this study, several previously developed GANs were investigated for prostate cancer (PCa) detection on T2-weighted (T2W) magnetic resonance ...

    • Computational Risk Analysis for Digitizing Sustainable Urban Water Supply Systems 

      Wu, Di (Doctoral theses at NTNU;2022:13, Doctoral thesis, 2022)
      The movement of global urbanization is severely challenging many aspects of our modem lives, especially after the 1960s. To address these spawned problems, in 2015, the United Nations published a series of Sustainable ...

    • Connectivity of underwater cognitive acoustic networks under spectrum constraint 

      Wang, Qiu; Dai, Hong-Ning; Wang, Hao; Wang, Qubeijian (Chapter, 2018)
      There is an extensive attention on underwater cognitive acoustic networks (UCANs) since acoustic spectrum becomes deficient owning to the proliferation of human activity in ocean. This paper presents an overview of our ...

    • ContractWard: Automated Vulnerability Detection Models for Ethereum Smart Contracts 

      Wang, Wei; Song, Jingjing; Xu, Guangquan; Li, Yidong; Wang, Hao; Su, Chunhua (Journal article, 2020)
      Smart contracts are decentralized applications running on Blockchain. A very large number of smart contracts has been deployed on Ethereum. Meanwhile, security flaws of contracts have led to huge pecuniary losses and ...

    • Control Strategy for Denitrification Efficiency of Coal-fired Power Plant Based on Deep Reinforcement Learning 

      Fu, Jigao; Xiao, Hong; Wang, Hao; Zhou, Junhao (Peer reviewed; Journal article, 2020)
      The optimal control of denitrification system in coal-fired power plants in China has recently received widespread attention. The accurate prediction of denitrification efficiency and formulate control strategy of ...

    • Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0 

      Wu, Yulei; Dai, Hong-Ning; Wang, Hao (Journal article; Peer reviewed, 2020)
      Critical infrastructure systems are vital to underpin the functioning of a society and economy. Due to ever-increasing number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data ...

    • Data-Driven Maritime Processes Management Using Executable Models 

      Richta, Tomáš; Wang, Hao; Osen, Ottar; Styve, Arne; Janoušek, Vladimír (Journal article, 2018)
      In this paper we describe a decision support system for maritime traffic and operations, based on formal models and driven by data from the environment. To handle the complexity of system description, we work with a ...

    • Data-driven Modeling of Ship Motion Prediction Based on Support Vector Regression 

      Kawan, Bikram; Wang, Hao; Li, Guoyuan; Chhantyal, Khim (Journal article; Peer reviewed, 2017)
      This paper presents a flexible system structure to analyze and model for the potential use of huge ship sensor data to generate efficient ship motion prediction model. The noisy raw data is cleaned using noise reduction, ...

    • Deep Learning Approaches in Credit Scoring 

      Hjelkrem, Lars Ole (Doctoral theses at NTNU;2023:256, Doctoral thesis, 2023)
      SUMMARY Credit scoring is a crucial aspect of the lending process, as it helps lenders to assess the creditworthiness of potential borrowers. The main focus of this thesis is applying deep learning methods on transaction ...

    • Deep Learning Enhanced Human Activity Recognition for Internet of Healthcare Things 

      Zhou, Xiaokang; Liang, Wei; Wang, Kevin I-Kai; Wang, Hao; Yang, Laurence T.; Jin, Qun (Peer reviewed; Journal article, 2020)
      Along with the advancement of several emerging computing paradigms and technologies, such as cloud computing, mobile computing, artificial intelligence, and big data, Internet of Things (IoT) technologies have been applied ...

    • Deep Learning for Low-Resource and Morphology-Rich Language Processing 

      Sun, Mengtao (Doctoral theses at NTNU;2023:50, Doctoral thesis, 2023)
      Since data-driven Natural Language Processing (NLP) approaches emerged in the late 60s, many practical applications have been proposed, such as automatic sentiment analyzers and named entity recognizers. Today, the robust ...

    • Deep Learning for Mobile Crowdsourcing Techniques, Methods, and Challenges: A Survey 

      Liu, Bingchen; Zhong, Weiyi; Xie, Jushi; Kong, Lingzhen; Yang, Yihong; Lin, Chuang; Wang, Hao (Peer reviewed; Journal article, 2021)
      With the ever-increasing popularity of mobile computing technology and the wide adoption of outsourcing strategy in labour-intensive industrial domains, mobile crowdsourcing has recently emerged as a promising resolution ...

    • Deep learning for privacy preservation in autonomous moving platforms enhanced 5G heterogeneous networks 

      Wu, Yulei; Ma, Yuxiang; Dai, Hong-Ning; Wang, Hao (Peer reviewed; Journal article, 2021)
      5G heterogeneous networks have become a promising platform to connect a growing number of Internet-of-Things (IoT) devices and accommodate a wide variety of vertical services. IoT has not been limited to traditional sensing ...

    • Detection and Classification of Moving Vehicle From Video Using Multiple Spatio-Temporal Features 

      Wang, Yu; Ban, Xiaojuan; Wang, Huan; Wu, Di; Wang, Hao; Yang, Shouqing; Liu, Sinuo; Lai, Jinhui (Journal article; Peer reviewed, 2019)
      The information acquisition and automatic processing technology based on visual surveillance sensors in intelligent transportation system (ITS) has become an important application field of computer vision technology. The ...

    • DHD-Net: A Novel Deep-Learning-based Dehazing Network 

      Xie, Liangru; Wang, Hao; Wang, Zhuowei; Cheng, Lianglun (Chapter, 2020)
      Eliminating haze interference in images is still a challenging problem. In this paper, we consider more systematically the physical hazing mechanisms, combined with deep learning, propose a new end-to-end dehazing network ...

    • DT-CP: A Double-TTPs Based Contract-signing Protocol with Lower Computational Cost 

      Xu, Guangquan; Zhang, Yao; Jiao, Litao; Panaousis, Emmanouil; Liang, Kaitai; Wang, Hao; Li, Xiaotong (Journal article; Peer reviewed, 2019)
      This paper characterizes a contract signing protocol with high efficiency in Internet of Things. Recent studies show that existing contract-signing protocols can achieve abuse-freeness and resist inference attack, but ...

    • Dual Calibration Mechanism based L2,p-Norm for Graph Matching 

      Yu, Yu-Feng; Xu, Guoxia; Huang, Ke-Kun; Zhu, Hu; Chen, Long; Wang, Hao (Peer reviewed; Journal article, 2020)
      Unbalanced geometric structure caused by variations with deformations, rotations and outliers is a critical issue that hinders correspondence establishment between image pairs in existing graph matching methods. To deal ...

    • Edge Computing-Enabled Resource Provisioning for Video Surveillance in Internet of Vehicles 

      Xu, Xiaolong; Wu, Qi; He, Chengxun; Wan, Shaohua; Qi, Lianyong; Wang, Hao (Journal article; Peer reviewed, 2019)
      As a novel technology, Internet of Vehicles (IoV) is employed to gather real-time traffic information for drivers from sensors and video surveillance devices with image processing, circumstances analysis and events ...

    • Efficient Video Privacy Protection Against Malicious Face Recognition Models 

      Guo, Enting; Li, Peng; Yu, Shui; Wang, Hao (Journal article; Peer reviewed, 2022)
      The proliferation of powerful facial recognition systems poses a serious threat to user privacy. Attackers could train highly accurate facial recognition models using public data on social platforms. Therefore, recent works ...