David J. Field

发表

Daniel J. Graham, David J. Field, D. Field, 2007 .

Wavelet-Like Receptive Fields Emerge From a Network That Learns Sparse Codes for Natural Images

David J. Field, Bruno A. Olshausen, Uris Hall, 1996 .

Wavelets, vision and the statistics of natural scenes

David J. Field, D. Field, David J. Field, 1999, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

What The Statistics Of Natural Images Tell Us About Visual Coding

David J. Field, D. Field, 1989, Photonics West - Lasers and Applications in Science and Engineering.

Towards a state-space geometry of neural responses to natural scenes: A steady-state approach

David J. Field, Michelle R. Greene, Vladimir Miskovic, 2019, NeuroImage.

Statistics of edge profiles in natural scenes

David J. Field, Damon M. Chandler, Kedarnath P. Vilankar, 2012 .

Sparse Coding of Natural Images Produces Localized, Oriented, Bandpass Receptive Fields

David J. Field, Bruno A. Olshausen, D. Field, 1995 .

Introduction: vision and brain

Stephen Grossberg, Leif H. Finkel, David J. Field, 2004 .

How sensitive are we to distortions in natural scenes

David J. Field, Adriana Olmos, Frederick A. A. Kingdom, 2004 .

Emergence of simple-cell receptive field properties by learning a sparse code for natural images

David J. Field, Bruno A. Olshausen, D. Field, 1996, Nature.

Wavelets, blur, and the sources of variability in the amplitude spectra of natural scenes

David J. Field, Bruno A. Olshausen, Nuala Brady, 1996, Electronic Imaging.

Decorrelation and response equalization with center-surround receptive fields

Daniel J. Graham, David J. Field, Damon M. Chandler, 2004 .

The Role of Hierarchy in Learning to Categorize Images

David J. Field, Shimon Edelman, Reza Shahbazi, 2011, CogSci.

On the statistics of soothing natural scenes

David J. Field, Elif Celikors, Nancy M. Wells, 2020 .

Vision and the Coding of Natural Images

Bruno A. Olshausen, David J. Field, Bruno A. Olshausen, 2000, American Scientist.

Contour integration across depth

David J. Field, Robert F. Hess, D. Field, 1995, Vision Research.

How Close Are We to Understanding V1?

David J. Field, Bruno A. Olshausen, D. Field, 2005, Neural Computation.

Revealing the hidden responses of a sparse coding network

David J. Field, Kedarnath P. Vilankar, James R. Golden, 2016 .

Finding a face on Mars: a study on the priors for illusory objects

David J. Field, Kedarnath P. Vilankar, 2016 .

What steady state visual evoked potentials (SSVEP) tell us about the early representation of natural scenes.

David J. Field, Michelle R. Greene, Bruce C. Hansen, 2019 .

Selective and invariant features of neural response surfaces measured with principal curvature

David J. Field, Kedarnath P. Vilankar, James R. Golden, 2019, bioRxiv.

What Is the Goal of Sensory Coding?

David J. Field, D. Field, 1994, Neural Computation.

Translation invariance with a contour integration task

David J. Field, Desmond C. Ong, Anthony Hayes, 2012 .

What Image Properties Regulate Eye Growth?

David J. Field, Serge O. Dumoulin, Robert F. Hess, 2006, Current Biology.

Visual coding, redundancy, and “feature detection”

David J. Field, 1998 .

Learning efficient linear codes for natural images: the roles of sparseness, overcompleteness, and statistical independence

David J. Field, Bruno A. Olshausen, 1996, Electronic Imaging.

Contour integration by the human visual system: Evidence for a local “association field”

David J. Field, Robert F. Hess, Anthony Hayes, 1993, Vision Research.

Towards a state-space geometry of neural responses to natural scenes: A steady-state approach

David J. Field, Michelle R. Greene, Vladimir Miskovic, 2019 .

Mapping the neuroelectric state-space geometry of natural scenes

David J. Field, Michelle R. Greene, Vladimir Miskovic, 2018 .

The sparse structure of natural chemical environments

David J. Field, Thomas A. Cleland, Marlene D. Berke, 2017, 2017 ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN).

An attempt towards a unified account of non-linearities in visual neurons

David J. Field, Michael Wu, D. Field, 2004 .

What is the other 85% of V1 doing?

David J. Field, Bruno A. Olshausen, D. Field, 2004 .

Sparse coding with an overcomplete basis set: A strategy employed by V1?

David J. Field, Bruno A. Olshausen, D. Field, 1997, Vision Research.

A geometric approach to sparse coding yields insight into nonlinear responses

David J. Field, Kedarnath P. Vilankar, James R. Golden, 2016 .

Global nonlinear compression of natural luminances in painted art

Daniel J. Graham, David J. Field, D. Field, 2008, Electronic Imaging.

A new model and a new demonstration of contrast sensitivity

David J. Field, Damon M. Chandler, 2020 .

A method of estimating the information content of natural scenes

David J. Field, Damon M. Chandler, D. Field, 2010 .

Matched filters, wavelets and the statistics of natural scenes

David J. Field, 1999 .

Can the theory of “whitening” explain the center-surround properties of retinal ganglion cell receptive fields?

Daniel J. Graham, David J. Field, Damon M. Chandler, 2006, Vision Research.

Innate Visual Learning through Spontaneous Activity Patterns

David J. Field, Mark V. Albert, Adam Schnabel, 2008, PLoS Comput. Biol..

Revealing the cortical transformations of real-world scenes using dynamic electrode-to-image (DETI) mapping

David J. Field, Michelle R. Greene, Bruce C. Hansen, 2021, Journal of Vision.

Contour integration in strabismic amblyopia: The sufficiency of an explanation based on positional uncertainty

David J. Field, William McIlhagga, Robert F. Hess, 1997, Vision Research.

Vision and brain : how the brains sees : new approaches to computer vision

Stephen Grossberg, Leif H. Finkel, David J. Field, 2004 .

Is the spatial deficit in strabismic amblyopia due to loss of cells or an uncalibrated disarray of cells?

David J. Field, Robert F. Hess, D. Field, 1994, Vision Research.

What Is the Other 85 Percent of V1 Doing

David J. Field, Bruno A. Olshausen, David J. Field, 2006 .

Natural Images: Coding Efficiency

David J. Field, D. Field, Daniel J. Graham, 2009 .