Publication

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Filters: Author is Josh H. McDermott  [Clear All Filters]
2016
Traer, J. & McDermott, J. H. Environmental statistics enable perceptual separation of sound and space. Speech and Audio in the Northeast (2016).
Mlynarski, W. & McDermott, J. H. Learning mid-level codes for natural sounds. Computational and Systems Neuroscience (Cosyne) 2016 (2016). at <http://www.cosyne.org/c/index.php?title=Cosyne2016_posters_2>PDF icon Wiktor_COSYNE_2015_hierarchy_final.pdf (2.52 MB)
Mlynarski, W. & McDermott, J. H. Learning Mid-Level Codes for Natural Sounds. Advances and Perspectives in Auditory Neuroscience (2016).PDF icon APAN_large_JHM kopia.pdf (19.74 MB)
Owens, A., Isola, P., McDermott, J. H., Freeman, W. T. & Torralba, A. Lecture Notes in Computer ScienceComputer Vision – ECCV 2016Ambient Sound Provides Supervision for Visual Learning. 14th European Conference on Computer Vision 801 - 816 (2016). doi:10.1007/978-3-319-46448-010.1007/978-3-319-46448-0_48
Mlynarski, W. & McDermott, J. H. Lossy Compression of Sound Texture by the Human Auditory System. Society for Neuroscience Meeting (2016).
Traer, J. & McDermott, J. H. Statistics of natural reverberation enable perceptual separation of sound and space. Proceedings of the National Academy of Sciences 113, E7856 - E7865 (2016).
Owens, A. et al. Visually indicated sounds. Conference on Computer Vision and Pattern Recognition (2016).PDF icon Owens_etal_2016_visually_indicated_sounds_CVPR.pdf (7.57 MB)