Neural engineering

Results: 553



#Item
21Supervised Phrase Table Triangulation with Neural Word Embeddings for Low-Resource Languages Tomer Levinboim and David Chiang Department of Computer Science and Engineering University of Notre Dame {levinboim.1,dchiang}@

Supervised Phrase Table Triangulation with Neural Word Embeddings for Low-Resource Languages Tomer Levinboim and David Chiang Department of Computer Science and Engineering University of Notre Dame {levinboim.1,dchiang}@

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Source URL: www.emnlp2015.org

- Date: 2015-12-05 04:09:49
    22Two Full Time PhD Positions in Biomedical Engineering at the University of Rhode Island The Neural Processing and Control Lab (NeuralPC Lab) at the University of Rhode Island (URI), Department of Electrical, Computer, an

    Two Full Time PhD Positions in Biomedical Engineering at the University of Rhode Island The Neural Processing and Control Lab (NeuralPC Lab) at the University of Rhode Island (URI), Department of Electrical, Computer, an

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    Source URL: www.ele.uri.edu

    - Date: 2016-12-05 13:05:43
      23SALICON: 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
        24Modeling the Visual Word Form Area Using a Deep Convolutional Neural Network Sandy Wiraatmadja () Department of Computer Science and Engineering, University of California San Diego 9500 Gilman Dr 0404, L

        Modeling the Visual Word Form Area Using a Deep Convolutional Neural Network Sandy Wiraatmadja () Department of Computer Science and Engineering, University of California San Diego 9500 Gilman Dr 0404, L

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        Source URL: mindmodeling.org

        - Date: 2016-08-03 11:42:52
          25A Deep Siamese Neural Network Learns the Human-Perceived Similarity Structure of Facial Expressions Without Explicit Categories Sanjeev Jagannatha Rao () Department of Computer Science and Engineering, Univ

          A Deep Siamese Neural Network Learns the Human-Perceived Similarity Structure of Facial Expressions Without Explicit Categories Sanjeev Jagannatha Rao () Department of Computer Science and Engineering, Univ

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          Source URL: mindmodeling.org

          - Date: 2016-08-03 11:42:36
            26Probabilistic Neural Programs arXiv:1612.00712v1 [cs.NE] 2 Dec 2016 Kenton W. Murray ∗ Department of Computer Science and Engineering

            Probabilistic Neural Programs arXiv:1612.00712v1 [cs.NE] 2 Dec 2016 Kenton W. Murray ∗ Department of Computer Science and Engineering

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            Source URL: arxiv.org

            - Date: 2016-12-04 20:27:23
              27Computers / Ordinateurs Neural Engineering: Unraveling The Complexities Of Neural Systems 1.0 An engineering approach to neuroscience ecently, several leaders in neuroscientific research have

              Computers / Ordinateurs Neural Engineering: Unraveling The Complexities Of Neural Systems 1.0 An engineering approach to neuroscience ecently, several leaders in neuroscientific research have

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              Source URL: www.ewh.ieee.org

              - Date: 2003-04-29 09:20:27
                28Project II Title: EFRI-COPN: Neuroscience and Neural Networks for Engineering the Future Intelligent Electric Power Grid (http://brain2grid.org) Investigators: Dr. G K Venayagamoorthy, Dr. D C Wunsch & Dr. K Corzine Bio-

                Project II Title: EFRI-COPN: Neuroscience and Neural Networks for Engineering the Future Intelligent Electric Power Grid (http://brain2grid.org) Investigators: Dr. G K Venayagamoorthy, Dr. D C Wunsch & Dr. K Corzine Bio-

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                Source URL: isc.mst.edu

                - Date: 2014-01-22 05:22:52
                  29STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES R. C. van Dalen, J. Yang, H. Wang, A. Ragni, C. Zhang, M. J. F. Gales Department of Engineering, University of Cambridge, United Kingdom ABSTRACT State-

                  STRUCTURED DISCRIMINATIVE MODELS USING DEEP NEURAL-NETWORK FEATURES R. C. van Dalen, J. Yang, H. Wang, A. Ragni, C. Zhang, M. J. F. Gales Department of Engineering, University of Cambridge, United Kingdom ABSTRACT State-

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                  Source URL: mi.eng.cam.ac.uk

                  - Date: 2015-11-28 19:03:51