Blar i SINTEF Open på forfatter "Srivastava, Gautam"

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    • Artificial intelligence of medical things for disease detection using ensemble deep learning and attention mechanism 

      Djenouri, Youcef; Belhadi, Asma; Yazidi, Anis; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      In this paper, we present a novel paradigm for disease detection. We build an artificial intelligence based system where various biomedical data are retrieved from distributed and homogeneous sensors. We use different deep ...

    • Deep learning based hashtag recommendation system for multimedia data 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This work aims to provide a novel hybrid architecture to suggest appropriate hashtags to a collection of orpheline tweets. The methodology starts with defining the collection of batches used in the convolutional neural ...

    • Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Djenouri, Djamel; Lin, Jerry Chun-Wei; Fortino, Giancarlo (Peer reviewed; Journal article, 2021)
      This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can ...

    • Deviation Point Curriculum Learning for Trajectory Outlier Detection in Cooperative Intelligent Transport Systems 

      Ahmed, Usman; Srivastava, Gautam; Djenouri, Youcef; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Cooperative Intelligent Transport Systems (C-ITS) are emerging in the field of transportation systems, which can be used to provide safety, sustainability, efficiency, communication and cooperation between vehicles, roadside ...

    • An edge-driven multi-agent optimization model for infectious disease detection 

      Djenouri, Youcef; Srivastava, Gautam; Yazidi, Anis; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This research work introduces a new intelligent framework for infectious disease detection by exploring various emerging and intelligent paradigms. We propose new deep learning architectures such as entity embedding networks, ...

    • Emergent Deep Learning for Anomaly Detection in Internet of Everything 

      Djenouri, Youcef; Djenouri, Djamel; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This research presents a new generic deep learning framework for anomaly detection in the Internet of Everything (IoE). It combines decomposition methods, deep neural networks, and evolutionary computation to better detect ...

    • An evolutionary model to mine high expected utility patterns from uncertain databases 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam; Yasin, Rizwan; Djenouri, Youcef (Peer reviewed; Journal article, 2021)
      In recent decades, mobile or the Internet of Thing (IoT) devices are dramatically increasing in many domains and applications. Thus, a massive amount of data is generated and produced. Those collected data contain a large ...

    • Fast and accurate convolution neural network for detecting manufacturing data 

      Djenouri, Youcef; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This article introduces a technique known as clustering with particle for object detection (CPOD) for use in smart factories. CPOD builds on regional-based methods to identify smart object data using outlier detection, ...

    • Fast and Accurate Deep Learning Framework for Secure Fault Diagnosis in the Industrial Internet of Things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Ghosh, Uttam; Chatterjee, Pushpita; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper introduced a new deep learning framework for fault diagnosis in electrical power systems. The framework integrates the convolution neural network and different regression models to visually identify which faults ...

    • Hybrid group anomaly detection for sequence data: application to trajectory data analytics 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Cano, Alberto; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Many research areas depend on group anomaly detection. The use of group anomaly detection can maintain and provide security and privacy to the data involved. This research attempts to solve the deficiency of the existing ...

    • Hybrid RESNET and Regional Convolution Neural Network Framework for Accident Estimation in Smart Roads 

      Djenouri, Youcef; Srivastava, Gautam; Djenouri, Djamel; Belhadi, Asma; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      Road safety is tackled and an intelligent deep learning framework is proposed in this work, which includes outlier detection, vehicle detection, and accident estimation. The road state is first collected, while an intelligent ...

    • Intelligent blockchain management for distributed knowledge graphs in IoT 5G environments 

      Djenouri, Youcef; Srivastava, Gautam; Belhadi, Asma; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This article introduces a new problem of distributed knowledge graph, in IoT 5G setting. We developed an end-to-end solution for solving such problem by exploring the blockchain management and intelligent method for producing ...

    • Intelligent Deep Fusion Network for Anomaly Identification in Maritime Transportation Systems 

      Djenouri, Youcef; Belhadi, Asma; Djenouri, Djamel; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This paper introduces a novel deep learning architecture for identifying outliers in the context of intelligent transportation systems. The use of a convolutional neural network with decomposition is explored to find ...

    • Intelligent Graph Convolutional Neural Network for Road Crack Detection 

      Djenouri, Youcef; Belhadi, Asma; Houssein, Essam H.; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This paper presents a novel intelligent system based on graph convolutional neural networks to study road crack detection in intelligent transportation systems. The visual features of the input images are first computed ...

    • Mining Profitable and Concise Patterns in Large-Scale Internet of Things Environments 

      Lin, Jerry Chun-Wei; Djenouri, Youcef; Srivastava, Gautam; Fournier-Viger, Philippe (Peer reviewed; Journal article, 2021)
      In recent years, HUIM (or a.k.a. high-utility itemset mining) can be seen as investigated in an extensive manner and studied in many applications especially in basket-market analysis and its relevant applications. Since ...

    • A nutrient recommendation system for soil fertilization based on evolutionary computation 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam; Djenouri, Youcef (Peer reviewed; Journal article, 2021)
      In agricultural production, soil characteristics play a vital role in maintaining fertility by allowing crops to develop better through root nutrition with minimal energy inputs. Nitrogen (N), Phosphorus (P), and Potassium ...

    • Privacy reinforcement learning for faults detection in the smart grid 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Jolfaei, Alireza; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Recent anticipated advancements in ad hoc Wireless Mesh Networks (WMN) have made them strong natural candidates for Smart Grid’s Neighborhood Area Network (NAN) and the ongoing work on Advanced Metering Infrastructure ...

    • Scalable Mining of High-Utility Sequential Patterns With Three-Tier MapReduce Model 

      Lin, Jerry Chun-Wei; Djenouri, Youcef; Srivastava, Gautam; Li, Yuanfa; Yu, Philip S. (Peer reviewed; Journal article, 2021)
      High-utility sequential pattern mining (HUSPM) is a hot research topic in recent decades since it combines both sequential and utility properties to reveal more information and knowledge rather than the traditional frequent ...

    • Secure Collaborative Augmented Reality Framework for Biomedical Informatics 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Augmented reality is currently a great interest in biomedical health informatics. At the same time, several challenges have been appeared, in particular with the rapid progress of smart sensors technologies, and medical ...

    • Sensor data fusion for the industrial artificial intelligence of things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Houssein, Essam H.; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      The emergence of smart sensors, artificial intelligence, and deep learning technologies yield artificial intelligence of things, also known as the AIoT. Sophisticated cooperation of these technologies is vital for the ...