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14 та иш

Иш: Enhancing Breast Cancer Diagnosis Through Segmentation-Driven Generative Adversarial Networks for Synthetic Mammogram Generation

  1. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

    Freddie Bray, Jacques Ferlay, Isabelle Soerjomataram +3

    Мақола201834 иқтибос
    ABI

  2. U-Net: Convolutional Networks for Biomedical Image Segmentation

    Olaf Ronneberger, Philipp Fischer, Thomas Brox

    Боб201532 иқтибос
    ABI

  3. Dermatologist-level classification of skin cancer with deep neural networks

    Andre Esteva, Brett Kuprel, Roberto A. Novoa +4

    Мақола201712 иқтибос
    ABI

  4. Сарлавҳасиз

    Бошқа7 иқтибос
    ABI

  5. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

    Hoo-Chang Shin, Holger R. Roth, Mingchen Gao +6

    Мақола20164 иқтибос
    ABI

  6. A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction

    Adam Yala, Constance D. Lehman, Tal Schuster +2

    Мақола20192 иқтибос
    ABI

  7. Unsupervised Representation Learning with Deep Convolutional Generative\n Adversarial Networks

    Alec Radford, Luke Metz, Soumith Chintala

    Препринт20152 иқтибос
    ABI

  8. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  9. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  10. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  11. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  12. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  13. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI

  14. Сарлавҳасиз

    Бошқа1 иқтибос
    ABI