Tags: deep learning

All Categories (1-8 of 8)

  1. Source code for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision

    2017-09-24 21:22:47 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu | doi:10.4231/R7V98675

    This document includes the main source code (Matlab or Python) related to our study.

    https://purr.purdue.edu/publications/2816

  2. Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 2

    2017-09-18 19:45:42 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu | doi:10.4231/R7NS0S1F

    This is a video-fMRI dataset for subject 2 (out of three) acquired by the Laboratory of Integrated Brain Imaging (LIBI).

    https://purr.purdue.edu/publications/2806

  3. Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests

    2017-09-15 15:14:52 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu | doi:10.4231/R7SF2TCW

    This is a video-fMRI dataset contains the videos with stimuli acquired by the Laboratory of Integrated Brain Imaging (LIBI).

    https://purr.purdue.edu/publications/2809

  4. Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 3

    2017-09-15 14:43:12 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu | doi:10.4231/R7J101BV

    This is a video-fMRI dataset for subject 3 (out of three) acquired by the Laboratory of Integrated Brain Imaging (LIBI).

    https://purr.purdue.edu/publications/2807

  5. Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Subject 1

    2017-09-15 13:28:40 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu | doi:10.4231/R7X63K3M

    This is a video-fMRI dataset for subject 1 (out of three) acquired by the Laboratory of Integrated Brain Imaging (LIBI),

    https://purr.purdue.edu/publications/2805

  6. Data for Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision Tests - Stimuli

    2017-09-15 13:24:22 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Yizhen Zhang, Kun-Han Lu, Jiayue Cao, Zhongming Liu | doi:10.4231/R71Z42KK

    This is a video-fMRI dataset contains the videos with stimuli acquired by the Laboratory of Integrated Brain Imaging (LIBI).

    https://purr.purdue.edu/publications/2808

  7. Visualized layer-wise visual features in deep residual neural network

    2017-06-29 12:24:17 | Datasets | Contributor(s): Haiguang Wen, Junxing Shi, Wei Chen, Zhongming Liu | doi:10.4231/R7PR7T1G

    Deep residual neural network is a brain-inspired computational model. 50 layers of neuron-like computational units are stacked into a bottom-up hierarchy. Features encoded at units are visualized for intuitively understanding the internal...

    https://purr.purdue.edu/publications/2590

  8. Simplicity of K-means versus deepness of Deep Learning. A Case of Unsupervised Feature Learning with Limited Data

    2015-09-30 20:07:55 | Datasets | Contributor(s): Murat Dundar, Qiang Kou, Baichuan Zhang, Yicheng He, Bartlomiej P. Rajwa | doi:10.4231/R7N58J9Z

    A study contrasting K-means-based unsupervised feature learning and deep learning techniques for small data sets with limited intra- as well as inter-class diversity

    https://purr.purdue.edu/publications/1988

The Purdue University Research Repository (PURR) is a university core research facility provided by the Purdue University Libraries, the Office of the Executive Vice President for Research and Partnerships, and Information Technology at Purdue (ITaP).