Výsledky vyhledávání - "Convolutional Variational Autoencoder (CVAE)"

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  1. 1

    A Zero-Shot Fault Detection Method for UAV Sensors Based on a Novel CVAE-GAN Model Autor Li, Chuanjiang, Luo, Kai, Yang, Lei, Li, Shaobo, Wang, Haoyu, Zhang, Xiangjie, Liao, Zihao

    ISSN: 1530-437X, 1558-1748
    Vydáno: New York IEEE 15.07.2024
    Vydáno v IEEE sensors journal (15.07.2024)
    “…Unmanned aerial vehicles (UAVs) have demonstrated remarkable versatility across a spectrum of missions, and their autonomous flight and real-time control…”
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  2. 2

    CNN-LSTM-Based Fault Diagnosis and Adaptive Multichannel Fusion Calibration of Filament Current Sensor for Mass Spectrometer Autor Li, Xinshuo, Li, Pinghua, Zhang, Zhen, Yin, Jiancheng, Sheng, Yunlong, Zhang, Luoxuan, Zhou, Wenxing, Zhuang, Xuye

    ISSN: 1530-437X, 1558-1748
    Vydáno: New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 15.01.2024
    Vydáno v IEEE sensors journal (15.01.2024)
    “…The mass spectrometer filament current sensor reflects the health status of the filament by detecting real-time variation in filament current, providing an…”
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  3. 3

    Unsupervised few shot learning architecture for diagnosis of periodontal disease in dental panoramic radiographs Autor Kim, Min Joo, Chae, Sun Geu, Bae, Suk Joo, Hwang, Kyung-Gyun

    ISSN: 2045-2322, 2045-2322
    Vydáno: London Nature Publishing Group UK 05.10.2024
    Vydáno v Scientific reports (05.10.2024)
    “…In the domain of medical imaging, the advent of deep learning has marked a significant progression, particularly in the nuanced area of periodontal disease…”
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  4. 4

    Automated construction of Wi-Fi-based indoor logical location predictor using crowd-sourced photos with Wi-Fi signals Autor Kumrai, Teerawat, Korpela, Joseph, Zhang, Yizhe, Ohara, Kazuya, Murakami, Tomoki, Abeysekera, Hirantha, Maekawa, Takuya

    ISSN: 1574-1192, 1873-1589
    Vydáno: Elsevier B.V 01.02.2023
    Vydáno v Pervasive and mobile computing (01.02.2023)
    “…Owing to the recent proliferation of smartphones and the SNS, a large number of images taken by smartphones at various places have been uploaded to SNSs. In…”
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  5. 5

    A multimodal deep fusion graph framework to detect social distancing violations and FCGs in pandemic surveillance Autor Varghese, Elizabeth B., Thampi, Sabu M.

    ISSN: 0952-1976, 1873-6769
    Vydáno: Elsevier Ltd 01.08.2021
    “…In pandemic surveillance, ensuring social distance has emerged as a challenging issue due to the lack of proper therapeutic agents, and this envisages the need…”
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  6. 6

    Learning Deep Features for Robotic Inference From Physical Interactions Autor Dehban, Atabak, Zhang, Shanghang, Cauli, Nino, Jamone, Lorenzo, Santos, Jose

    ISSN: 2379-8920, 2379-8939
    Vydáno: Piscataway IEEE 01.09.2023
    “…In order to effectively handle multiple tasks that are not predefined, a robotic agent needs to automatically map its high-dimensional sensory inputs into…”
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  7. 7

    Deep Learning Techniques for Radar-Based Continuous Human Activity Recognition Autor Mehta, Ruchita, Sharifzadeh, Sara, Palade, Vasile, Tan, Bo, Daneshkhah, Alireza, Karayaneva, Yordanka

    ISSN: 2504-4990, 2504-4990
    Vydáno: Basel MDPI AG 01.12.2023
    “…Human capability to perform routine tasks declines with age and age-related problems. Remote human activity recognition (HAR) is beneficial for regular…”
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  8. 8

    Anomaly Detection in Hyperspectral Image Using 3D-Convolutional Variational Autoencoder Autor Zhang, Jingfa, Xu, Yang, Zhan, Tianming, Wu, Zebin, Wei, Zhihui

    ISSN: 2153-7003
    Vydáno: IEEE 11.07.2021
    “…Anomaly detection (AD) has become a hot topic in hyperspectral image (HSI) analysis. Anomalies are samples that are significantly different from the…”
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  9. 9

    Continuous Human Activity Recognition using Radar Imagery and Dynamic Time Warping Autor Mehta, Ruchita, Palade, Vasile, Sharifzadeh, Sara, Tan, Bo, Karayaneva, Yordanka

    Vydáno: IEEE 01.12.2022
    “…Remote Human Activity Recognition (HAR) in a private residential area has a beneficial influence on the elderly population's life, since this group of people…”
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