Year |
Citation |
Score |
2020 |
Oess T, Ernst MO, Neumann H. Computational principles of neural adaptation for binaural signal integration. Plos Computational Biology. 16: e1008020. PMID 32678847 DOI: 10.1371/Journal.Pcbi.1008020 |
0.367 |
|
2020 |
Oess T, Löhr MPR, Schmid D, Ernst MO, Neumann H. From Near-Optimal Bayesian Integration to Neuromorphic Hardware: A Neural Network Model of Multisensory Integration. Frontiers in Neurorobotics. 14: 29. PMID 32499692 DOI: 10.3389/Fnbot.2020.00029 |
0.41 |
|
2019 |
Habtegiorgis SW, Jarvers C, Rifai K, Neumann H, Wahl S. The Role of Bottom-Up and Top-Down Cortical Interactions in Adaptation to Natural Scene Statistics. Frontiers in Neural Circuits. 13: 9. PMID 30814934 DOI: 10.3389/Fncir.2019.00009 |
0.382 |
|
2019 |
Löhr MPR, Schmid D, Neumann H. Motion Integration and Disambiguation concerted by Feedforward-Feedback Interactions of V1-MT-MSTl Journal of Vision. 19. DOI: 10.1167/19.10.167C |
0.328 |
|
2019 |
Jarvers C, Neumann H. A compartmental model of feedback modulation in visual cortex Journal of Vision. 19. DOI: 10.1167/19.10.108D |
0.356 |
|
2018 |
Layher G, Neumann H. Points and Stripes: A Novel Technique for Masking Biological Motion Point-Light Stimuli. Frontiers in Psychology. 9: 1455. PMID 30210382 DOI: 10.3389/Fpsyg.2018.01455 |
0.405 |
|
2018 |
Saeed A, Al-Hamadi A, Neumann H. Facial point localization via neural networks in a cascade regression framework Multimedia Tools and Applications. 77: 2261-2283. DOI: 10.1007/S11042-016-4261-X |
0.311 |
|
2017 |
Layher G, Brosch T, Neumann H. Real-Time Biologically Inspired Action Recognition from Key Poses Using a Neuromorphic Architecture. Frontiers in Neurorobotics. 11: 13. PMID 28381998 DOI: 10.3389/Fnbot.2017.00013 |
0.365 |
|
2016 |
Gomez O, Neumann H. Biologically Inspired Model for Inference of 3D Shape from Texture. Plos One. 11: e0160868. PMID 27649387 DOI: 10.1371/Journal.Pone.0160868 |
0.381 |
|
2015 |
Abdul-Kreem LI, Neumann H. Neural Mechanisms of Cortical Motion Computation Based on a Neuromorphic Sensory System. Plos One. 10: e0142488. PMID 26554589 DOI: 10.1371/Journal.Pone.0142488 |
0.446 |
|
2015 |
Brosch T, Neumann H, Roelfsema PR. Reinforcement Learning of Linking and Tracing Contours in Recurrent Neural Networks. Plos Computational Biology. 11: e1004489. PMID 26496502 DOI: 10.1371/Journal.Pcbi.1004489 |
0.391 |
|
2015 |
Schrodt F, Layher G, Neumann H, Butz MV. Embodied learning of a generative neural model for biological motion perception and inference. Frontiers in Computational Neuroscience. 9: 79. PMID 26217215 DOI: 10.3389/Fncom.2015.00079 |
0.409 |
|
2015 |
Brosch T, Tschechne S, Neumann H. On event-based optical flow detection. Frontiers in Neuroscience. 9: 137. PMID 25941470 DOI: 10.3389/Fnins.2015.00137 |
0.375 |
|
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 |
0.35 |
|
2015 |
Rodríguez-Sánchez AJ, Neumann H, Piater JH. Beyond Simple and Complex Neurons: Towards Intermediate-level Representations of Shapes and Objects KüNstliche Intelligenz. 29: 19-29. DOI: 10.1007/S13218-014-0341-0 |
0.325 |
|
2014 |
Layher G, Schrodt F, Butz MV, Neumann H. Adaptive learning in a compartmental model of visual cortex-how feedback enables stable category learning and refinement. Frontiers in Psychology. 5: 1287. PMID 25538637 DOI: 10.3389/Fpsyg.2014.01287 |
0.349 |
|
2014 |
Brosch T, Neumann H. Computing with a canonical neural circuits model with pool normalization and modulating feedback. Neural Computation. 26: 2735-89. PMID 25248083 DOI: 10.1162/Neco_A_00675 |
0.37 |
|
2014 |
Tschechne S, Neumann H. Hierarchical representation of shapes in visual cortex-from localized features to figural shape segregation. Frontiers in Computational Neuroscience. 8: 93. PMID 25157228 DOI: 10.3389/Fncom.2014.00093 |
0.453 |
|
2014 |
Brosch T, Neumann H. Interaction of feedforward and feedback streams in visual cortex in a firing-rate model of columnar computations. Neural Networks : the Official Journal of the International Neural Network Society. 54: 11-6. PMID 24632344 DOI: 10.1016/J.Neunet.2014.02.005 |
0.416 |
|
2014 |
Tschechne S, Neumann H. Unified representation of motion and motion streak patterns in a model of cortical form-motion interaction Journal of Vision. 14: 18-18. DOI: 10.1167/14.10.18 |
0.343 |
|
2014 |
Layher G, Giese MA, Neumann H. Learning representations of animated motion sequences-a neural model Topics in Cognitive Science. 6: 170-182. DOI: 10.1111/Tops.12075 |
0.392 |
|
2013 |
Raudies F, Ringbauer S, Neumann H. A bio-inspired, computational model suggests velocity gradients of optic flow locally encode ordinal depth at surface borders and globally they encode self-motion. Neural Computation. 25: 2421-49. PMID 23663150 DOI: 10.1162/Neco_A_00479 |
0.359 |
|
2013 |
Raudies F, Neumann H. Modeling heading and path perception from optic flow in the case of independently moving objects. Frontiers in Behavioral Neuroscience. 7: 23. PMID 23554589 DOI: 10.3389/Fnbeh.2013.00023 |
0.331 |
|
2013 |
Layher G, Neumann H. Combining form and motion - an integrated approach for learning biological motion representations Journal of Vision. 13: 194-194. DOI: 10.1167/13.9.194 |
0.321 |
|
2012 |
Raudies F, Neumann H. A bio-inspired, motion-based analysis of crowd behavior attributes relevance to motion transparency, velocity gradients, and motion patterns. Plos One. 7: e53456. PMID 23300930 DOI: 10.1371/Journal.Pone.0053456 |
0.357 |
|
2012 |
Poort J, Raudies F, Wannig A, Lamme VA, Neumann H, Roelfsema PR. The role of attention in figure-ground segregation in areas V1 and V4 of the visual cortex. Neuron. 75: 143-56. PMID 22794268 DOI: 10.1016/J.Neuron.2012.04.032 |
0.402 |
|
2012 |
Brosch T, Neumann H. Perceptual Crowding in a Neural Model of Feedforward-Feedback Interactions Journal of Vision. 12: 329-329. DOI: 10.1167/12.9.329 |
0.347 |
|
2012 |
Layher G, Neumann H. Neural mechanisms of action recognition and implied motion Journal of Vision. 12: 142-142. DOI: 10.1167/12.9.142 |
0.323 |
|
2012 |
Niese R, Al-Hamadi A, Farag A, Neumann H, Michaelis B. Facial expression recognition based on geometric and optical flow features in colour image sequences Iet Computer Vision. 6: 79-89. DOI: 10.1049/Iet-Cvi.2011.0064 |
0.319 |
|
2012 |
Raudies F, Neumann H. A review and evaluation of methods estimating ego-motion Computer Vision and Image Understanding. 116: 606-633. DOI: 10.1016/J.Cviu.2011.04.004 |
0.392 |
|
2011 |
Raudies F, Mingolla E, Neumann H. A model of motion transparency processing with local center-surround interactions and feedback. Neural Computation. 23: 2868-914. PMID 21851277 DOI: 10.1162/Neco_A_00193 |
0.348 |
|
2011 |
Beck C, Neumann H. Combining feature selection and integration--a neural model for MT motion selectivity. Plos One. 6: e21254. PMID 21814543 DOI: 10.1371/Journal.Pone.0021254 |
0.431 |
|
2011 |
Raudies F, Mingolla E, Neumann H. Motion transparency and spatial integration size – a modeling study F1000research. 11: 751-751. DOI: 10.7490/F1000Research.1276.1 |
0.322 |
|
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 |
0.474 |
|
2010 |
Raudies F, Neumann H. A neural model of the temporal dynamics of figure-ground segregation in motion perception. Neural Networks : the Official Journal of the International Neural Network Society. 23: 160-76. PMID 19931405 DOI: 10.1016/J.Neunet.2009.10.005 |
0.456 |
|
2010 |
Beck C, Neumann H. Interactions of motion and form in visual cortex - A neural model. Journal of Physiology, Paris. 104: 61-70. PMID 19909811 DOI: 10.1016/J.Jphysparis.2009.11.005 |
0.41 |
|
2010 |
Raudies F, Neumann H. A model of neural mechanisms in monocular transparent motion perception. Journal of Physiology, Paris. 104: 71-83. PMID 19900543 DOI: 10.1016/J.Jphysparis.2009.11.010 |
0.411 |
|
2010 |
Weidenbacher U, Neumann H. The first spike counts: A model for STDP learning pose specific representations for estimating view direction Journal of Vision. 8: 161-161. DOI: 10.1167/8.6.161 |
0.301 |
|
2010 |
Bayerl P, Neumann H. Feature attention in motion perception - a computational account Journal of Vision. 6: 513-513. DOI: 10.1167/6.6.513 |
0.346 |
|
2010 |
Weidenbacher U, Bayerl P, Neumann H. Generation of sketch-like feature encodings in oriented faces - A neural model Journal of Vision. 6: 1069-1069. DOI: 10.1167/6.6.1069 |
0.33 |
|
2010 |
Bayerl P, Neumann H. Attention and figure-ground segregation in a model of motion perception Journal of Vision. 5: 659-659. DOI: 10.1167/5.8.659 |
0.364 |
|
2010 |
Bayerl PAJ, Neumann H. Recurrent processing in the dorsal pathway underlies the robust integration and segregation of motion patterns Journal of Vision. 2: 658-658. DOI: 10.1167/2.7.658 |
0.328 |
|
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 |
0.451 |
|
2010 |
Raudies F, Mingolla E, Neumann H. A Neural Model of Binocular Transparent Depth Perception Journal of Vision. 10: 377-377. DOI: 10.1167/10.7.377 |
0.359 |
|
2010 |
Ringbauer S, Raudies F, Neumann H. Local Perceptual Learning for Motion Pattern Discrimination: a Neural Model Journal of Vision. 10: 1110-1110. DOI: 10.1167/10.7.1110 |
0.351 |
|
2009 |
Allen HA, Humphreys GW, Colin J, Neumann H. Ventral extra-striate cortical areas are required for human visual texture segmentation. Journal of Vision. 9: 2.1-14. PMID 19761335 DOI: 10.1167/9.9.2 |
0.337 |
|
2009 |
Weidenbacher U, Neumann H. Extraction of surface-related features in a recurrent model of V1-V2 interactions. Plos One. 4: e5909. PMID 19526061 DOI: 10.1371/Journal.Pone.0005909 |
0.398 |
|
2008 |
Beck C, Ognibeni T, Neumann H. Object segmentation from motion discontinuities and temporal occlusions--a biologically inspired model. Plos One. 3: e3807. PMID 19043613 DOI: 10.1371/Journal.Pone.0003807 |
0.402 |
|
2008 |
Hansen T, Neumann H. A recurrent model of contour integration in primary visual cortex. Journal of Vision. 8: 8.1-25. PMID 18831631 DOI: 10.1167/8.8.8 |
0.671 |
|
2008 |
Thielscher A, Neumann H. Globally consistent depth sorting of overlapping 2D surfaces in a model using local recurrent interactions. Biological Cybernetics. 98: 305-37. PMID 18317794 DOI: 10.1007/S00422-008-0211-7 |
0.408 |
|
2008 |
Thielscher A, Kölle M, Neumann H, Spitzer M, Grön G. Texture segmentation in human perception: a combined modeling and fMRI study. Neuroscience. 151: 730-6. PMID 18191901 DOI: 10.1016/J.Neuroscience.2007.11.040 |
0.433 |
|
2008 |
Neumann H, Pessoa L, Hansen T. Interaction of on and off pathways for visual contrast measurement (Biological Cybernetics (1999) 81 (515-532) DOI: 10.1007/s004220050580) Biological Cybernetics. 98: 353. DOI: 10.1007/s00422-008-0225-1 |
0.59 |
|
2007 |
Bayerl P, Neumann H. A neural model of feature attention in motion perception. Bio Systems. 89: 208-15. PMID 17280774 DOI: 10.1016/J.Biosystems.2006.04.018 |
0.405 |
|
2007 |
Bayerl P, Neumann H. A fast biologically inspired algorithm for recurrent motion estimation. Ieee Transactions On Pattern Analysis and Machine Intelligence. 29: 246-60. PMID 17170478 DOI: 10.1109/Tpami.2007.24 |
0.408 |
|
2007 |
Thielscher A, Neumann H. A computational model to link psychophysics and cortical cell activation patterns in human texture processing. Journal of Computational Neuroscience. 22: 255-282. PMID 17103312 DOI: 10.1007/S10827-006-0011-9 |
0.435 |
|
2007 |
Carranza N, Cristóbal G, Bayerl P, Neumann H. Motion estimation of magnetic resonance cardiac images using the Wigner-Ville and hough transforms Optics and Spectroscopy (English Translation of Optika I Spektroskopiya). 103: 877-885. DOI: 10.1134/S0030400X07120077 |
0.34 |
|
2007 |
Fischer S, Bayerl P, Neumann H, Redondo R, Cristóbal G. Iterated tensor voting and curvature improvement Signal Processing. 87: 2503-2515. DOI: 10.1016/J.Sigpro.2007.03.019 |
0.302 |
|
2007 |
Neumann H, Yazdanbakhsh A, Mingolla E. Seeing surfaces: The brain's vision of the world Physics of Life Reviews. 4: 189-222. DOI: 10.1016/J.Plrev.2007.09.001 |
0.606 |
|
2007 |
Bayerl P, Neumann H. Disambiguating Visual Motion by Form-Motion Interaction--a Computational Model International Journal of Computer Vision. 72: 27-45. DOI: 10.1007/S11263-006-8891-8 |
0.411 |
|
2006 |
Keil MS, Cristóbal G, Neumann H. Gradient representation and perception in the early visual system--a novel account of Mach band formation. Vision Research. 46: 2659-74. PMID 16603218 DOI: 10.1016/J.Visres.2006.01.038 |
0.391 |
|
2005 |
Keil MS, Cristóbal G, Hansen T, Neumann H. Recovering real-world images from single-scale boundaries with a novel filling-in architecture. Neural Networks : the Official Journal of the International Neural Network Society. 18: 1319-31. PMID 16039097 DOI: 10.1016/J.Neunet.2005.04.003 |
0.638 |
|
2005 |
Thielscher A, Neumann H. Neural mechanisms of human texture processing: texture boundary detection and visual search. Spatial Vision. 18: 227-57. PMID 15856938 DOI: 10.1163/1568568053320594 |
0.441 |
|
2004 |
Bayerl P, Neumann H. Disambiguating visual motion through contextual feedback modulation. Neural Computation. 16: 2041-66. PMID 15333206 DOI: 10.1162/0899766041732404 |
0.441 |
|
2004 |
Hansen T, Neumann H. A simple cell model with dominating opponent inhibition for robust image processing. Neural Networks : the Official Journal of the International Neural Network Society. 17: 647-62. PMID 15288890 DOI: 10.1016/J.Neunet.2004.04.002 |
0.669 |
|
2004 |
Hansen T, Neumann H. Neural mechanisms for the robust representation of junctions. Neural Computation. 16: 1013-37. PMID 15070508 DOI: 10.1162/089976604773135087 |
0.668 |
|
2003 |
Thielscher A, Neumann H. Neural mechanisms of cortico-cortical interaction in texture boundary detection: a modeling approach. Neuroscience. 122: 921-939. PMID 14643761 DOI: 10.1016/J.Neuroscience.2003.08.050 |
0.455 |
|
2003 |
Keil MS, Cristobal G, Neumann H. Novel theory on mach-bands and gradient formation in early vision Proceedings of Spie. 5119: 316-324. DOI: 10.1117/12.499072 |
0.379 |
|
2002 |
Hansen T, Neumann H. A computational model of recurrent, colinear long-range interaction in VI for contour enhancement and junction detection Journal of Vision. 2: 106a. DOI: 10.1167/2.7.106 |
0.312 |
|
2001 |
Neumann H, Pessoa L, Hansen T. Visual filling-in for computing perceptual surface properties. Biological Cybernetics. 85: 355-69. PMID 11721990 DOI: 10.1007/S004220100258 |
0.673 |
|
2001 |
Neumann H, Mingolla E. 12 Computational neural models of spatial integration in perceptual grouping Advances in Psychology. 130: 353-400. DOI: 10.1016/S0166-4115(01)80032-7 |
0.383 |
|
2001 |
Hansen T, Sepp W, Neumann H. Recurrent Long-Range Interactions in Early Vision Lecture Notes in Computer Science. 127-138. DOI: 10.1007/3-540-44597-8_9 |
0.664 |
|
2001 |
Hansen T, Neumann H. Neural Mechanisms for Representing Surface and Contour Features Lecture Notes in Computer Science. 139-153. DOI: 10.1007/3-540-44597-8_10 |
0.67 |
|
2000 |
Baratoff G, Toepfer C, Neumann H. Combined space-variant maps for optical-flow-based navigation Biological Cybernetics. 83: 199-209. PMID 11007296 DOI: 10.1007/S004220000164 |
0.308 |
|
2000 |
Hansen T, Baratoff G, Neumann H. A simple cell model with dominating opponent inhibition for robust contrast detection Kognitionswissenschaft. 9: 93-100. DOI: 10.1007/Bf03354941 |
0.588 |
|
2000 |
Baratoff G, Schönfelder R, Ahrns I, Neumann H. Orientation Contrast Detection in Space-Variant Images Lecture Notes in Computer Science. 554-563. DOI: 10.1007/3-540-45482-9_56 |
0.395 |
|
1999 |
Neumann H, Pessoa L, Hansen T, Hanse T. Interaction of ON and OFF pathways for visual contrast measurement. Biological Cybernetics. 81: 515-32. PMID 10592025 DOI: 10.1007/S00422-008-0225-1 |
0.668 |
|
1999 |
Neumann H, Sepp W. Recurrent V1-V2 interaction in early visual boundary processing. Biological Cybernetics. 81: 425-444. PMID 10592018 DOI: 10.1007/S004220050573 |
0.43 |
|
1998 |
Pessoa L, Neumann H. Why does the brain fill in? Trends in Cognitive Sciences. 2: 422-4. PMID 21227268 DOI: 10.1016/S1364-6613(98)01237-6 |
0.374 |
|
1998 |
Neumann H. Representations, computation, and inverse ecological optics Behavioral and Brain Sciences. 21: 766-767. DOI: 10.1017/S0140525X98431753 |
0.301 |
|
1998 |
Neumann H, Pessoa L, Mingolla E. A neural architecture of brightness perception: Non-linear contrast detection and geometry-driven diffusion Image and Vision Computing. 16: 423-446. DOI: 10.1016/S0262-8856(97)00085-1 |
0.418 |
|
1997 |
Gilchrist ID, Humphreys GW, Riddoch MJ, Neumann H. Luminance and edge information in grouping: a study using visual search. Journal of Experimental Psychology. Human Perception and Performance. 23: 464-80. PMID 9104005 DOI: 10.1037//0096-1523.23.2.464 |
0.325 |
|
1997 |
Pessoa L, Grunewald A, Neumann H, Littmann E. A Biological Neural Network of Visual Cell Responses: Static and Motion Processing Journal of the Brazilian Computer Society. 4. DOI: 10.1590/S0104-65001997000200002 |
0.69 |
|
1996 |
Neumann H. Mechanisms of Neural Architecture for Visual Contrast and Brightness Perception. Neural Networks : the Official Journal of the International Neural Network Society. 9: 921-936. PMID 12662572 DOI: 10.1016/0893-6080(96)00023-8 |
0.374 |
|
1996 |
Neumann H, Mössner P. Neural Mechanisms in Boundary Grouping, Illusory Contour Generation, and Spatial Tuning of Receptive Field Selectivity Perception. 25: 108-108. DOI: 10.1068/V96L0703 |
0.317 |
|
1995 |
Pessoa L, Mingolla E, Neumann H. A contrast- and luminance-driven multiscale network model of brightness perception. Vision Research. 35: 2201-23. PMID 7667932 DOI: 10.1016/0042-6989(94)00313-0 |
0.4 |
|
1994 |
Ludwig K, Neumann H, Neumann B. Local stereoscopic depth estimation Image and Vision Computing. 12: 16-35. DOI: 10.1016/0262-8856(94)90052-3 |
0.36 |
|
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