Depth

Results: 6281



#Item
701

Build Depth of Knowledge with RAFT Activities

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Source URL: www.raft.net

Language: English - Date: 2014-01-30 12:06:21
    702

    2013 IEEE Conference on Computer Vision and Pattern Recognition Fusing Depth from Defocus and Stereo with Coded Apertures Yuichi Takeda Osaka University

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    Source URL: www.cv-foundation.org

    Language: English - Date: 2013-06-08 15:23:31
      703

      Short Paper: Autonomous Depth Adjustment for Underwater Sensor Networks Carrick Detweiler1 , Marek Doniec, Iuliu Vasilescu, Elizabeth Basha, and Daniela Rus Distributed Robotics Laboratory, CSAIL MIT {carrick,doniec,iul

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      Source URL: cse.unl.edu

      Language: English - Date: 2010-09-02 12:45:05
        704Computer graphics / Digital photography / Imaging / Electrical engineering / Digital signal processing / Image processing / Signal processing / Light field / Pixel / Rendering / Digital camera / Sampling

        ONLINE VIEW SAMPLING FOR ESTIMATING DEPTH FROM LIGHT FIELDS Changil Kim?† Kartic Subr? ?

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        Source URL: graphics.ethz.ch

        Language: English - Date: 2016-03-10 17:06:33
        705

        Depth, Dimension and Resolutions in Commutative Algebra Claire Tête PhD student in Poitiers MAP, May 2014

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        Source URL: perso.crans.org

        Language: English - Date: 2014-06-17 06:14:57
          706

          エディントン限界:再考 Eddington Limit for a Gaseous Stratus with Finite Optical Depth 福江 純@大阪教育大学

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          Source URL: quasar.cc.osaka-kyoiku.ac.jp

          Language: Japanese - Date: 2015-04-30 20:27:03
            707Time-of-flight camera / Artificial intelligence / Kinect / Camera / Red Digital Cinema Camera Company / Stereo cameras / Range imaging

            Three Depth-Camera Technologies Compared Fabrizio Pece1 and Jan Kautz1 and Tim Weyrich1 1 1

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            Source URL: www0.cs.ucl.ac.uk

            Language: English - Date: 2013-02-20 17:58:36
            708

            Hitting Depth: Investigating Robustness to Adversarial Examples in Deep Convolutional Neural Networks Chris Billovits Stanford University Mihail Eric

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            Source URL: cs231n.stanford.edu

            Language: English - Date: 2016-03-23 18:05:39
              709

              Rock and Wood | 1day (all levels) No painting experience necessary - No sewing machine Build a landscape that creates depth and dimension for your composition. Strategic placement of hand dyed multi-value fabrics will si

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              Source URL: esteritaaustin.com

              Language: English - Date: 2012-06-20 01:35:15
                710

                Creating the Illusion of Depth | 1day (all levels) Fusing class- No sewing machine In this workshop you’ll train your eye and sharpen your design ability. Learn how to create the illusion of depth through an architectu

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                Source URL: esteritaaustin.com

                Language: English - Date: 2012-06-20 01:35:11
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