Výsledky vyhľadávania - "encoder and decoder network"

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  1. 1

    Two-stage convolutional encoder-decoder network to improve the performance and reliability of deep learning models for topology optimization Autor Ates, Gorkem Can, Gorguluarslan, Recep M.

    ISSN: 1615-147X, 1615-1488
    Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2021
    “…A vital necessity when employing state-of-the-art deep neural networks (DNNs) for topology optimization is to predict near-optimal structures while satisfying…”
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    Journal Article
  2. 2

    Nonrigid Structure-From-Motion via Differential Geometry With Recoverable Conformal Scale Autor Chen, Yongbo, Zhang, Yanhao, Parashar, Shaifali, Zhao, Liang, Huang, Shoudong

    ISSN: 1552-3098, 1941-0468
    Vydavateľské údaje: IEEE 2025
    “…Nonrigid structure-from-motion (NRSfM), a promising technique for addressing the mapping challenges in monocular visual deformable simultaneous localization…”
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    Journal Article
  3. 3

    ED-Dehaze Net: Encoder and Decoder Dehaze Network Autor Zhang, Hongqi, Wei, Yixiong, Zhou, Hongqiao, Wu, Qianhao

    ISSN: 1989-1660, 1989-1660
    Vydavateľské údaje: IMAI Software 01.09.2022
    “…The presence of haze will significantly reduce the quality of images, such as resulting in lower contrast and blurry details. This paper proposes a novel…”
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    Journal Article
  4. 4

    Cultural and Creative Product Design based on Target-Embedding Variational Autoencoder and Convolutional Neural Network Autor Wang, Chunwei

    Vydavateľské údaje: IEEE 24.01.2025
    “…The integration of the traditional cultural elements with the contemporary designs defines the process of Cultural and Creative Products Design (CCPD). The…”
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  5. 5

    An Encoder-Sequencer-Decoder Network for Lane Detection to Facilitate Autonomous Driving Autor Hussain, Muhammad Ishfaq, Rafique, Muhammad Aasim, Ko, Yeongmin, Khan, Zafran, Olimov, Farrukh, Naz, Zubia, Kim, Jeongbae, Jeon, Moongu

    ISSN: 2642-3901
    Vydavateľské údaje: ICROS 17.10.2023
    “…Lane detection in all weather conditions is a pressing necessity for autonomous driving. Accurate lane detection ensures the safe operation of autonomous…”
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  6. 6

    Roadway Crack Segmentation Based on an Encoder-decoder Deep Network with Multi-scale Convolutional Blocks Autor Sun, Mengyuan, Guo, Runhua, Zhu, Jinhui, Fan, Wenhui

    Vydavateľské údaje: IEEE 01.01.2020
    “…In highway pavement management, to detect and segment cracks are the key distresses in the condition evaluation. Considering the characteristics of imbalance,…”
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