Blar i Kristiania Open Archive 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 ...

    • BIoMT-ISeg: Blockchain internet of medical things for intelligent segmentation 

      Belhadi, Asma; Holland, Jon-Olav; Yazidi, Anis; Srivastava, Gautam; Lin, Jerry Chun-Wei; Djenouri, Youcef (Peer reviewed; Journal article, 2023)
      In the quest of training complicated medical data for Internet of Medical Things (IoMT) scenarios, this study develops an end-to-end intelligent framework that incorporates ensemble learning, genetic algorithms, blockchain ...

    • 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 ...

    • 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 ...

    • 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)
      Abstract: 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 ...

    • 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)
      Abstract: 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 ...

    • Interpretable intrusion detection for next generation of Internet of Things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei; Yazidi, Anis (Peer reviewed; Journal article, 2023)
      This paper presents a new framework for intrusion detection in the next-generation Internet of Things. MinMax normalization strategy is used to collect and preprocess data. The Marine Predator algorithm is then used to ...

    • 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 ...

    • Reinforcement learning multi-agent system for faults diagnosis of mircoservices in industrial settings 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper develops a new framework called MASAD (Multi-Agents System for Anomaly Detection), a hybrid combination of reinforcement learning, and a multi-agents system to identify abnormal behaviors of microservices in ...

    • 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 ...

    • SS-ITS: secure scalable intelligent transportation systems 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)

    • A sustainable deep learning framework for fault detection in 6G Industry 4.0 heterogeneous data environments 

      Mezair, Tinhinane; Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      Abstract The integration of 5G and Beyond 5G (B5G)/6G in Machine-to-Machine (M2M) communications, is making Industry 4.0 smarter. However, the goal of having a sustainable self-monitored industry has not been reached yet. ...

    • Toward a Cognitive-Inspired Hashtag Recommendation for Twitter Data Analysis 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      Abstract: This research investigates hashtag suggestions in a heterogeneous and huge social network, as well as a cognitive-based deep learning solution based on distributed knowledge graphs. Community detection is first ...

    • Vehicle detection using improved region convolution neural network for accident prevention in smart roads 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Djenouri, Djamel; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This paper explores the vehicle detection problem and introduces an improved regional convolution neural network. The vehicle data (set of images) is first collected, from which the noise (set of outlier images) is removed ...

    • When explainable AI meets IoT applications for supervised learning 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This paper introduces a novel and complete framework for solving different Internet of Things (IoT) applications, which explores eXplainable AI (XAI), deep learning, and evolutionary computation. The IoT data coming from ...