Výsledky vyhľadávania - "Shared autoencoder"

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  1. 1

    Shared Autoencoder Gaussian Process Latent Variable Model for Visual Classification Autor Li, Jinxing, Zhang, Bob, Zhang, David

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydavateľské údaje: United States IEEE 01.09.2018
    “… Different from the previous work on the GPLVM, the proposed shared autoencoder Gaussian process (SAGP…”
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    Journal Article
  2. 2

    Harmonization Shared Autoencoder Gaussian Process Latent Variable Model With Relaxed Hamming Distance Autor Li, Jinxing, Zhang, Bob, Lu, Guangming, Xu, Yong, Wu, Feng, Zhang, David

    ISSN: 2162-237X, 2162-2388, 2162-2388
    Vydavateľské údaje: Piscataway IEEE 01.11.2021
    “… To tackle these two issues, in this article, we propose a novel harmonization shared autoencoder GPLVM with a relaxed…”
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    Journal Article
  3. 3

    Reconstructing natural images from human fMRI by alternating encoding and decoding with shared autoencoder regularization Autor Qiao, Kai, Chen, Jian, Wang, Linyuan, Zhang, Chi, Tong, Li, Yan, Bin

    ISSN: 1746-8094, 1746-8108
    Vydavateľské údaje: Elsevier Ltd 01.03.2022
    “…•We proposed the mutual promotion of visual encoding and reconstruction models.•We designed alternating optimization bassed on seim-supervised learning.•We…”
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  4. 4

    Anomaly detection in images with shared autoencoders Autor Jia, Haoyang, Liu, Wenfen

    ISSN: 1662-5218, 1662-5218
    Vydavateľské údaje: Switzerland Frontiers Research Foundation 04.01.2023
    Vydané v Frontiers in neurorobotics (04.01.2023)
    “…Anomaly detection is a classical problem in computer vision, namely the determination of the normal from the abnormal when datasets are highly biased toward…”
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  5. 5

    Variable Rate Deep Image Compression With Modulated Autoencoder Autor Yang, Fei, Herranz, Luis, Weijer, Joost van de, Guitian, Jose A. Iglesias, Lopez, Antonio M., Mozerov, Mikhail G.

    ISSN: 1070-9908, 1558-2361
    Vydavateľské údaje: New York IEEE 2020
    “… Scaling the bottleneck representation of a shared autoencoder can provide variable rate compression with a single shared autoencoder…”
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  6. 6

    Learning Cross-Modality Representations From Multi-Modal Images Autor van Tulder, Gijs, de Bruijne, Marleen

    ISSN: 0278-0062, 1558-254X, 1558-254X
    Vydavateľské údaje: United States IEEE 01.02.2019
    Vydané v IEEE transactions on medical imaging (01.02.2019)
    “…Machine learning algorithms can have difficulties adapting to data from different sources, for example from different imaging modalities. We present and…”
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  7. 7

    SplineGen: Approximating unorganized points through generative AI Autor Zou, Qiang, Zhu, Lizhen, Wu, Jiayu, Yang, Zhijie

    ISSN: 0010-4485
    Vydavateľské údaje: Elsevier Ltd 01.01.2025
    Vydané v Computer aided design (01.01.2025)
    “… It first adopts a shared autoencoder model to learn a 512-D embedding for each input point, which has the local neighborhood…”
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  8. 8

    itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection Autor Cho, Hyeon, Choi, Junyong, Baek, Geonwoo, Hwang, Wonjun

    ISSN: 1063-6919
    Vydavateľské údaje: IEEE 01.06.2023
    “… To learn the map-view feature of a teacher network, the features from teacher and student networks are independently passed through the shared autoencoder…”
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    Konferenčný príspevok..
  9. 9

    Variable Rate Deep Image Compression with Modulated Autoencoder Autor Yang, Fei, Herranz, Luis, van de Weijer, Joost, Iglesias Guitián, José A, López, Antonio, Mozerov, Mikhail

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 21.07.2020
    Vydané v arXiv.org (21.07.2020)
    “… Scaling the bottleneck representation of a shared autoencoder can provide variable rate compression with a single shared autoencoder…”
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  10. 10

    itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection Autor Cho, Hyeon, Choi, Junyong, Baek, Geonwoo, Hwang, Wonjun

    ISSN: 2331-8422
    Vydavateľské údaje: Ithaca Cornell University Library, arXiv.org 27.03.2023
    Vydané v arXiv.org (27.03.2023)
    “… To learn the map-view feature of a teacher network, the features from teacher and student networks are independently passed through the shared autoencoder…”
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    Paper