Výsledky vyhledávání - "Mish function"

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  1. 1

    A novel deep learning based method for COVID-19 detection from CT image Autor JavadiMoghaddam, SeyyedMohammad, Gholamalinejad, Hossain

    ISSN: 1746-8094, 1746-8108, 1746-8094
    Vydáno: England Elsevier Ltd 01.09.2021
    “…The novel Coronavirus named COVID-19 that World Health Organization (WHO) announced as a pandemic rapidly spread worldwide. Fast diagnosis of the virus…”
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    Journal Article
  2. 2

    Combining raw data and engineered features for optimizing encrypted and compressed internet of things traffic classification Autor Saleh, Mariam M., AlSlaiman, Muhanned, Salman, Mohammed I., Wang, Bin

    ISSN: 0167-4048, 1872-6208
    Vydáno: Elsevier Ltd 01.07.2023
    Vydáno v Computers & security (01.07.2023)
    “…The Internet of Things (IoT) is used in many fields that generate sensitive data, such as healthcare and surveillance. The increased reliance on IoT raised…”
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    Journal Article
  3. 3

    Face Recognition Based on Improved Residual Network and Channel Attention Autor Jingfang Zeng, Li, Jieyu, Feng, Linlang

    ISSN: 0146-4116, 1558-108X
    Vydáno: Moscow Pleiades Publishing 01.10.2022
    “…With the continuous development of deep learning, convolutional neural networks have achieved good results in the field of face recognition. However, deep…”
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    Journal Article
  4. 4

    Improved Feature Point and Descriptor Extraction Network for SuperPoint Autor Suo, Qihan, Yan, Changqing, Liu, Chi, Ma, Chenyin

    ISSN: 2693-2776
    Vydáno: IEEE 16.12.2022
    “…Image feature point and descriptor extraction is the basis of SLAM, SFM and 3D reconstruction tasks. In this paper, we study the SuperPoint network, which has…”
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  5. 5

    An Improved MVCNN for 3D Shape Recognition Autor Wang, Yan, Zhong, Wanxia, Su, Hang, Zheng, Fujiang, Pang, Yiran, Wen, Hongchuan, Cai, Kun

    Vydáno: IEEE 22.11.2021
    “…The multi-view convolutional neural network architecture represented by MVCNN has achieved great success in 3D shape recognition. Taking the MVCNN architecture…”
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    Konferenční příspěvek