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Implicit privacy preservation: a framework based on data generation
Security and Safety, 2022 This paper addresses a special and imperceptible class of privacy, called implicit privacy. In contrast to traditional (explicit) privacy, implicit privacy has two essential properties: (1) It is not initially defined as a privacy attribute; (2) it is ...
Yang Qing +4 more
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Multiple Hypothesis Detection and Tracking Using Deep Learning for Video Traffic Surveillance
IEEE Access, 2021 Moroccan Intelligent Transport System is the first Moroccan system that uses the latest advances in computer vision, machine learning and deep learning techniques to manage Moroccan traffic and road violations. In this paper, we propose a fully automatic
Hamd Ait Abdelali +4 more
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Self-Supervised Joint Learning Fault Diagnosis Method Based on Three-Channel Vibration Images
Sensors, 2021 The accuracy of bearing fault diagnosis is of great significance for the reliable operation of rotating machinery. In recent years, increasing attention has been paid to intelligent fault diagnosis techniques based on deep learning.
Weiwei Zhang, Deji Chen, Yang Kong
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Byzantine-robust federated learning via credibility assessment on non-IID data
Mathematical Biosciences and Engineering, 2022 Federated learning is a novel framework that enables resource-constrained edge devices to jointly learn a model, which solves the problem of data protection and data islands.
Kun Zhai +3 more
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Multi-Task Autoencoders and Transfer Learning for Day-Ahead Wind and Photovoltaic Power Forecasts
Energies, 2022 Integrating new renewable energy resources requires robust and reliable forecasts to ensure a stable electrical grid and avoid blackouts. Sophisticated representation learning techniques, such as autoencoders, play an essential role, as they allow for ...
Jens Schreiber, Bernhard Sick
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Algorithms, 2023 During an emergency rescue operation, rescuers have to deal with many different health complications like cardiovascular, respiratory, neurological, psychiatric, etc.
Abu Shad Ahammed +2 more
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IEEE Access, 2023 It is extremely important to build a reasonable traffic network structure for traffic flow prediction. Owing to the complexity and dynamic of traffic networks, the graph neural network model has become one of the most effective methods for mining the ...
Xiaohui Cheng +3 more
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, 2022 In this chapter, we will provide a description of existing open-source operating systems (OSs) which have been analyzed with the objective of providing a porting for the reference architecture described in Chapter 2. Among the various possibilities, the ERIKA Enterprise RTOS (Real-Time Operating System) and Linux with preemption patches have been ...
Scordino C. +5 more
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Differentiable Architecture Search Algorithm Based on Global Comparison
IEEE Access, 2023 Manually building neural network models is a great test of researchers’ knowledge reserves, so using Neural Architecture Search (NAS) to automatically construct neural networks is becoming increasingly popular.
Xianglun Zeng, Hongxiang Xiao
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Sdn+K8s Routing Optimization Strategy in 5G Cloud Edge Collaboration Scenario
IEEE Access, 2023 The cloud-edge-collaboration framework in the 5G scenario emerged as the times developing. The horizontal and vertical disassembly of computing power is particularly important, relying on the full life cycle resource allocation and flexible configuration
Chungang Yan, Shuo Sheng
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