Deep foundation

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1The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

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Source URL: www.linuxfoundation.jp

- Date: 2018-03-23 20:34:23
    2The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

    The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

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    Source URL: www.linuxfoundation.org

    - Date: 2018-03-23 20:34:23
      3The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

      The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

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      Source URL: www.linuxfoundation.org

      - Date: 2018-03-23 20:34:23
        4The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

        The LF Deep Learning Foundation Charter The Linux Foundation Effective March 26, Mission and Scope of the LF Deep Learning Foundation. a) The primary mission of the LF Deep Learning Foundation (the “Directed Fu

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        Source URL: www.linuxfoundation.jp

        - Date: 2018-03-23 20:34:23
          5Deep Packet Anonymization Michael Foukarakis, Demetres Antoniades, Michalis Polychronakis Institute of Computer Science Foundation for Research and Technology—Hellas Heraklion, Crete, Greece

          Deep Packet Anonymization Michael Foukarakis, Demetres Antoniades, Michalis Polychronakis Institute of Computer Science Foundation for Research and Technology—Hellas Heraklion, Crete, Greece

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          Source URL: www.ics.forth.gr

          - Date: 2012-03-22 09:28:01
            6Deep Networks for Image Super-Resolution with Sparse Prior Zhaowen Wang†‡ Ding Liu† Jianchao Yang§ Wei Han† Thomas Huang† † Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL ‡ Adobe

            Deep Networks for Image Super-Resolution with Sparse Prior Zhaowen Wang†‡ Ding Liu† Jianchao Yang§ Wei Han† Thomas Huang† † Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL ‡ Adobe

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            Source URL: www.cv-foundation.org

            - Date: 2015-10-24 14:59:52
              7Video Super-Resolution via Deep Draft-Ensemble Learning Renjie Liao† Xin Tao† Ruiyu Li†

              Video Super-Resolution via Deep Draft-Ensemble Learning Renjie Liao† Xin Tao† Ruiyu Li†

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              Source URL: www.cv-foundation.org

              - Date: 2015-10-24 15:03:10
                8High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and its Applications to High-Level Vision Gedas Bertasius University of Pennsylvania

                High-for-Low and Low-for-High: Efficient Boundary Detection from Deep Object Features and its Applications to High-Level Vision Gedas Bertasius University of Pennsylvania

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                Source URL: www.cv-foundation.org

                - Date: 2015-10-24 15:01:50
                  9Semantic Pose using Deep Networks Trained on Synthetic RGB-D Jeremie Papon and Markus Schoeler Bernstein Center for Computational Neuroscience (BCCN) III. Physikalisches Institut - Biophysik, Georg-August University of G

                  Semantic Pose using Deep Networks Trained on Synthetic RGB-D Jeremie Papon and Markus Schoeler Bernstein Center for Computational Neuroscience (BCCN) III. Physikalisches Institut - Biophysik, Georg-August University of G

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                  Source URL: www.cv-foundation.org

                  - Date: 2015-10-24 15:06:33
                    10SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks Xun Huang1,2† Chengyao Shen1 Xavier Boix1,3 Qi Zhao1∗ 1 Department of Electrical and Computer Engineering, National Universi

                    SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks Xun Huang1,2† Chengyao Shen1 Xavier Boix1,3 Qi Zhao1∗ 1 Department of Electrical and Computer Engineering, National Universi

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                    Source URL: www.cv-foundation.org

                    - Date: 2015-10-24 14:57:44