Daniela Pamplona
Title
Cited by
Cited by
Year
Pan-retinal characterisation of light responses from ganglion cells in the developing mouse retina
G Hilgen, S Pirmoradian, D Pamplona, P Kornprobst, B Cessac, ...
Scientific reports 7 (1), 1-14, 2017
302017
PRANAS: a new platform for retinal analysis and simulation
B Cessac, P Kornprobst, S Kraria, H Nasser, D Pamplona, G Portelli, ...
Frontiers in neuroinformatics 11, 49, 2017
222017
Smooth foveal vision with gaussian receptive fields
D Pamplona, A Bernardino
2009 9th IEEE-RAS International Conference on Humanoid Robots, 223-229, 2009
162009
Power spectra of the natural input to the visual system
D Pamplona, J Triesch, CA Rothkopf
Vision research 83, 66-75, 2013
122013
A super-resolution approach for receptive fields estimation of neuronal ensembles
D Pamplona, G Hilgen, B Cessac, E Sernagor, P Kornprobst
BMC Neuroscience 16 (1), 1-2, 2015
72015
A Gabor wavelet pyramid-based object detection algorithm
YD Sato, J Jitsev, J Bornschein, D Pamplona, C Keck, ...
International Symposium on Neural Networks, 232-240, 2011
52011
ENAS: A new software for spike train analysis and simulation
B Cessac, P Kornprobst, S Kraria, H Nasser, D Pamplona, G Portelli, ...
Bernstein conference, Sept, 2016
42016
The effect of retinal GABA Depletion by Allylglycine on mouse retinal ganglion cell responses to light
G Hilgen, S Softley, D Pamplona, P Kornprobst, B Cessac, E Sernagor
European Retina Meeting, 2015
12015
Naturally Constrained Online Expectation Maximization
D Pamplona, A Manzanera
International Conference on Pattern Recognition (ICPR 2020), 2021
2021
Large visual neuron assemblies receptive fields estimation using a super-resolution approach
D Pamplona, G Hilgen, M Hennig, B Cessac, E Sernagor, P Kornprobst
Inria-Sophia antipolis, 2020
2020
Vision: Images, Signals and Neural Networks Models of Neural Processing in Visual Perception
J Blahuta, T Soukup, J Skacel, B Cessac, P Kornprobst, S Kraria, ...
Retina, 2015
2015
Shifting stimulus for faster receptive fields estimation of ensembles of neurons
D Pamplona, B Cessac, P Kornprobst
Computational and Systems Neuroscience (Cosyne), 2015
2015
Kornprobst P. A super-resolution approach for receptive fields estimation of
D Pamplona, G Hilgen, S Pirmoradian, MH Hennig, B Cessac, E Sernagor
2015
Can the imaging process explain ganglion cells anisotropies?
D Pamplona, J Triesch, CA Rothkopf
Perception ECVP abstract 42, 144-144, 2013
2013
The statistics of looking: Deriving properties of retinal ganglion cells across the visual field
D Pamplona, J Triesch, CA Rothkopf
Journal of Vision 12 (9), 771-771, 2012
2012
Eyes are not cameras: Deriving properties of retinal ganglion cells from the natural input
DG Pamplona, J Triesch, CA Rothkopf
Front. Comput. Neurosci. Conference Abstract: Bernstein Conference, 2012
2012
Edge and image statistics across the visual field
D Pamplona, J Triesch, CA Rothkopf
Front. Comput. Neurosci. Conference Abstract: BC11: Computational …, 2011
2011
25aTD-6 All Object Detection System Based on a Physiologically Plausible Gabor Pyramid
S YD, J Jitsev, J Bomschein, D Pamplona, C Keck, C von der Malsburg
Meeting Abstracts of the Physical Society of Japan 65.2. 2, 272, 2010
2010
Gaussian Foveation
D Pamplona
2008
on mouse retinal ganglion cell responses to light
G Hilgen, S Softley, D Pamplona, P Kornprobst, B Cessac, E Sernagor
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Articles 1–20