| Year |
Citation |
Score |
| 2018 |
Benzi M, Escobar M, Kornprobst P. A bio-inspired synergistic virtual retina model for tone mapping Computer Vision and Image Understanding. 168: 21-36. DOI: 10.1016/J.Cviu.2017.11.013 |
0.386 |
|
| 2017 |
Cessac B, Kornprobst P, Kraria S, Nasser H, Pamplona D, Portelli G, Viéville T. PRANAS: A New Platform for Retinal Analysis and Simulation. Frontiers in Neuroinformatics. 11: 49. PMID 28919854 DOI: 10.3389/Fninf.2017.00049 |
0.763 |
|
| 2017 |
Medathati NVK, Rankin J, Meso AI, Kornprobst P, Masson GS. Recurrent network dynamics reconciles visual motion segmentation and integration. Scientific Reports. 7: 11270. PMID 28900120 DOI: 10.1038/S41598-017-11373-Z |
0.594 |
|
| 2016 |
Meso AI, Rankin J, Faugeras O, Kornprobst P, Masson GS. The relative contribution of noise and adaptation to competition during tri-stable motion perception. Journal of Vision. 16: 6. PMID 27936270 DOI: 10.1167/16.15.6 |
0.544 |
|
| 2016 |
Masquelier T, Portelli G, Kornprobst P. Microsaccades enable efficient synchrony-based coding in the retina: a simulation study. Scientific Reports. 6: 24086. PMID 27063867 DOI: 10.1038/Srep24086 |
0.321 |
|
| 2016 |
Drogoul A, Aubert G, Cessac B, Kornprobst P. A new nonconvex variational approach for sensory neurons receptive field estimation Journal of Physics: Conference Series. 756: 012006. DOI: 10.1088/1742-6596/756/1/012006 |
0.445 |
|
| 2015 |
Pamplona D, Hilgen G, Cessac B, Sernagor E, Kornprobst P. A super-resolution approach for receptive fields estimation of neuronal ensembles Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P130 |
0.345 |
|
| 2015 |
Solari F, Chessa M, Medathati NVK, Kornprobst P. What can we expect from a V1-MT feedforward architecture for optical flow estimation? Signal Processing: Image Communication. DOI: 10.1016/J.Image.2015.04.006 |
0.419 |
|
| 2015 |
Medathati NVK, Neumann H, Masson GS, Kornprobst P. Bio-inspired computer vision: Towards a synergistic approach of artificial and biological vision Computer Vision and Image Understanding. 150: 1-30. DOI: 10.1016/J.Cviu.2016.04.009 |
0.502 |
|
| 2014 |
Rankin J, Meso AI, Masson GS, Faugeras O, Kornprobst P. Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration. Journal of Computational Neuroscience. 36: 193-213. PMID 24014258 DOI: 10.1007/S10827-013-0465-5 |
0.58 |
|
| 2014 |
Masquelier T, Portelli G, Kornprobst P. Microsaccades enable efficient synchrony-based visual feature learning and detection Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P121 |
0.333 |
|
| 2014 |
Portelli G, Barrett J, Sernagor E, Masquelier T, Kornprobst P. Rapid neural coding in the mouse retina with the first wave of spikes Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P120 |
0.321 |
|
| 2013 |
Rankin J, Tlapale E, Veltz R, Faugeras O, Kornprobst P. Bifurcation analysis applied to a model of motion integration with a multistable stimulus. Journal of Computational Neuroscience. 34: 103-24. PMID 22870848 DOI: 10.1007/S10827-012-0409-5 |
0.781 |
|
| 2013 |
Escobar M, Toledo PF, Masson GS, Kornprobst P. MT Motion integration can be explained by the spatiotemporal frequency content of V1 surround suppression Journal of Vision. 13: 362-362. DOI: 10.1167/13.9.362 |
0.356 |
|
| 2013 |
Masmoudi K, Antonini M, Kornprobst P. Streaming an image through the eye: The retina seen as a dithered scalable image coder Signal Processing: Image Communication. 28: 856-869. DOI: 10.1016/J.Image.2012.07.005 |
0.34 |
|
| 2012 |
Masmoudi K, Antonini M, Kornprobst P. Frames for exact inversion of the rank order coder. Ieee Transactions On Neural Networks and Learning Systems. 23: 353-9. PMID 24808514 DOI: 10.1109/Tnnls.2011.2179557 |
0.348 |
|
| 2012 |
Rankin J, Meso AI, Masson GS, Faugeras O, Kornprobst P. Perceptual transition dynamics of a multi-stable visual motion stimulus II: modelling Journal of Vision. 12: 749-749. DOI: 10.1167/12.9.749 |
0.547 |
|
| 2012 |
Meso AI, Rankin J, Kornprobst P, Faugeras O, Masson G. Perceptual transition dynamics of a multi-stable visual motion stimulus I: experiments Journal of Vision. 12: 748-748. DOI: 10.1167/12.9.748 |
0.556 |
|
| 2012 |
Rankin J, Meso A, Masson GS, Faugeras O, Kornprobst P. Motion direction integration following the onset of multistable stimuli (II): stability properties explain dynamic shifts in the dominant perceived direction Perception. 41: 24-24. DOI: 10.1068/V120175 |
0.363 |
|
| 2012 |
Escobar MJ, Kornprobst P. Action recognition via bio-inspired features: The richness of center-surround interaction Computer Vision and Image Understanding. 116: 593-605. DOI: 10.1016/J.Cviu.2012.01.002 |
0.392 |
|
| 2012 |
Tlapale E, Kornprobst P, Bouecke JD, Neumann H, Masson GS. Evaluating motion estimation models from behavioural and psychophysical data Lecture Notes of the Institute For Computer Sciences, Social-Informatics and Telecommunications Engineering. 87: 483-496. DOI: 10.1007/978-3-642-32615-8_46 |
0.766 |
|
| 2011 |
Escobar M, Toledo PF, Masson GS, Kornprobst P. How MT neurons get influenced by V1 surround suppression F1000research. 2. DOI: 10.7490/F1000Research.2199.1 |
0.402 |
|
| 2011 |
Neumann H, Bouecke JD, Tlapale E, Kornprobst P. Neural mechanisms of motion detection, integration, and segregation: From biology to artificial image processing systems Eurasip Journal On Advances in Signal Processing. 2011. DOI: 10.1155/2011/781561 |
0.795 |
|
| 2011 |
Ramírez-Manzanares A, Rivera M, Kornprobst P, Lauze F. Variational multi-valued velocity field estimation for transparent sequences Journal of Mathematical Imaging and Vision. 40: 285-304. DOI: 10.1007/S10851-011-0260-8 |
0.337 |
|
| 2011 |
Tlapale E, Kornprobst P, Masson GS, Faugeras O. A Neural Field Model for Motion Estimation Springer Proceedings in Mathematics. 5: 159-179. DOI: 10.1007/978-3-642-19604-1_9 |
0.512 |
|
| 2010 |
Tlapale E, Masson GS, Kornprobst P. Modelling the dynamics of motion integration with a new luminance-gated diffusion mechanism. Vision Research. 50: 1676-92. PMID 20553965 DOI: 10.1016/J.Visres.2010.05.022 |
0.781 |
|
| 2010 |
Tlapale E, Masson GS, Kornprobst P. A dynamical neural model of motion integration Journal of Vision. 10: 843-843. DOI: 10.1167/10.7.843 |
0.473 |
|
| 2010 |
Kornprobst P, Tlapale E, Bouecke J, Neumann H, Masson GS. A Bio-Inspired Evaluation Methodology for Motion Estimation Journal of Vision. 10: 835-835. DOI: 10.1167/10.7.835 |
0.468 |
|
| 2009 |
Wohrer A, Kornprobst P. Virtual Retina: a biological retina model and simulator, with contrast gain control. Journal of Computational Neuroscience. 26: 219-49. PMID 18670870 DOI: 10.1007/S10827-008-0108-4 |
0.751 |
|
| 2009 |
Aubert G, Kornprobst P. Can the nonlocal characterization of sobolev spaces by bourgain et al. be useful for solving variational problems? Siam Journal On Numerical Analysis. 47: 844-860. DOI: 10.1137/070696751 |
0.491 |
|
| 2009 |
Escobar MJ, Masson GS, Vieville T, Kornprobst P. Action recognition using a bio-inspired feedforward spiking network International Journal of Computer Vision. 82: 284-301. DOI: 10.1007/S11263-008-0201-1 |
0.767 |
|
| 2007 |
Viéville T, Chemla S, Kornprobst P. How do high-level specifications of the brain relate to variational approaches? Journal of Physiology, Paris. 101: 118-35. PMID 18035526 DOI: 10.1016/J.Jphysparis.2007.10.010 |
0.33 |
|
| 2007 |
Rochel O, Kornprobst P, Vieville T. Experimenting the variational definition of neural map computation Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P179 |
0.742 |
|
| 2007 |
Escobar M, Kornprobst P, Vieville T. Spike to spike MT model and applications Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P150 |
0.762 |
|
| 2007 |
Chemla S, Chavane F, Vieville T, Kornprobst P. Biophysical cortical column model for optical signal analysis Bmc Neuroscience. 8. DOI: 10.1186/1471-2202-8-S2-P140 |
0.769 |
|
| 2006 |
Escobar MJ, Wohrer A, Kornprobst P, Viéville T. Biological motion recognition using a MT-like model 3rd Ieee Latin American Robotics Symposium, Lars'06. 47-52. DOI: 10.1109/LARS.2006.334317 |
0.76 |
|
| 2006 |
Wohrer A, Masson G, Perrinet L, Kornprobst P, Viéville T. Contrast sensitivity adaptation in a virtual spiking retina and its comparison with mammalian retinas Perception. 35: 0-0. DOI: 10.1068/V060573 |
0.498 |
|
| 2006 |
Wohrer A, Kornprobst P, Viéville T. From light to spikes: A large-scale retina simulator Ieee International Conference On Neural Networks - Conference Proceedings. 4562-4570. |
0.721 |
|
| 2006 |
Viéville T, Kornprobst P. Modeling cortical maps with feed-backs Ieee International Conference On Neural Networks - Conference Proceedings. 110-117. |
0.745 |
|
| 2004 |
Faugeras O, Adde G, Charpiat G, Chefd'hotel C, Clerc M, Deneux T, Deriche R, Hermosillo G, Keriven R, Kornprobst P, Kybic J, Lenglet C, Lopez-Perez L, Papadopoulo T, Pons JP, et al. Variational, geometric, and statistical methods for modeling brain anatomy and function. Neuroimage. 23: S46-55. PMID 15501100 DOI: 10.1016/J.Neuroimage.2004.07.015 |
0.569 |
|
| 2004 |
Peeters RR, Kornprobst P, Nikolova M, Sunaert S, Vieville T, Malandain G, Deriche R, Faugeras O, Ng M, Van Hecke P. The use of super-resolution techniques to reduce slice thickness in functional MRI International Journal of Imaging Systems and Technology. 14: 131-138. DOI: 10.1002/Ima.20016 |
0.748 |
|
| 2003 |
Deriche R, Kornprobst P, Nikolova M, Ng M. Half-quadratic regularization for MRI image restoration Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 6: 585-588. |
0.485 |
|
| 2003 |
Lacombe C, Aubert G, Blanc-Féraucd L, Kornprobst P. Filtering interferometric phase images by anisotropic diffusion Ieee International Conference On Image Processing. 3: 141-144. |
0.428 |
|
| 2003 |
Kornprobst P, Peelers R, Nikolova M, Deriche R, Ng M, Van Hecke P. A superresolution framework for fMRI sequences and its impact on resulting activation maps Lecture Notes in Computer Science. 2879: 117-125. |
0.467 |
|
| 2002 |
Lacombe C, Kornprobst P, Aubert G, Blanc-Feraud L. A variational approach to one dimensional phase unwrapping Proceedings - International Conference On Pattern Recognition. 16: 810-813. |
0.404 |
|
| 1999 |
Aubert G, Deriche R, Kornprobst P. Computing optical flow via variational techniques Siam Journal On Applied Mathematics. 60: 156-182. DOI: 10.1137/S0036139998340170 |
0.659 |
|
| 1999 |
Kornprobst P, Deriche R, Aubert G. Image sequence analysis via partial differential equations Journal of Mathematical Imaging and Vision. 11: 5-26. DOI: 10.1023/A:1008318126505 |
0.701 |
|
| 1999 |
Aubert G, Kornprobst P. A mathematical study of the relaxed optical flow problem in the space BV (Ω) Siam Journal On Mathematical Analysis. 30: 1282-1308. |
0.407 |
|
| 1998 |
Kornprobst P, Deriche R, Aubert G. Mage sequence restoration: A PDE based coupled method for image restoration and motion segmentation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1407: 548-562. DOI: 10.1007/BFb0054764 |
0.655 |
|
| 1997 |
Kornprobst P, Deriche R, Aubert G. Image restoration via PDE Proceedings of Spie - the International Society For Optical Engineering. 2942: 22-33. DOI: 10.1117/12.267177 |
0.607 |
|
| 1997 |
Kornprobst P, Deriche R, Aubert G. Image coupling, restoration and enhancement via PDE's Ieee International Conference On Image Processing. 2: 458-461. |
0.604 |
|
| 1997 |
Kornprobst P, Deriche R, Aubert G. Nonlinear operators in image restoration Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 325-330. |
0.593 |
|
| 1996 |
Deriche R, Kornprobst P, Aubert G. Optical-flow estimation while preserving its discontinuities: A variational approach Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1035: 69-80. |
0.584 |
|
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