Year |
Citation |
Score |
2024 |
Pochinok I, Stöber TM, Triesch J, Chini M, Hanganu-Opatz IL. A developmental increase of inhibition promotes the emergence of hippocampal ripples. Nature Communications. 15: 738. PMID 38272901 DOI: 10.1038/s41467-024-44983-z |
0.762 |
|
2023 |
Rothkopf C, Bremmer F, Fiehler K, Dobs K, Triesch J. Models of vision need some action. The Behavioral and Brain Sciences. 46: e405. PMID 38054279 DOI: 10.1017/S0140525X23001577 |
0.727 |
|
2023 |
Tang Y, Triesch J, Deák GO. Variability in infant social responsiveness: Age and situational differences in attention-following. Developmental Cognitive Neuroscience. 63: 101283. PMID 37586147 DOI: 10.1016/j.dcn.2023.101283 |
0.597 |
|
2023 |
Schneider M, Bird AD, Gidon A, Triesch J, Jedlicka P, Cuntz H. Biological complexity facilitates tuning of the neuronal parameter space. Plos Computational Biology. 19: e1011212. PMID 37399220 DOI: 10.1371/journal.pcbi.1011212 |
0.466 |
|
2023 |
Stöber TM, Batulin D, Triesch J, Narayanan R, Jedlicka P. Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair. Communications Biology. 6: 479. PMID 37137938 DOI: 10.1038/s42003-023-04823-0 |
0.755 |
|
2022 |
Batulin D, Lagzi F, Vezzani A, Jedlicka P, Triesch J. A mathematical model of neuroimmune interactions in epileptogenesis for discovering treatment strategies. Iscience. 25: 104343. PMID 35601918 DOI: 10.1016/j.isci.2022.104343 |
0.504 |
|
2021 |
Vieth M, Stöber TM, Triesch J. PymoNNto: A Flexible Modular Toolbox for Designing Brain-Inspired Neural Networks. Frontiers in Neuroinformatics. 15: 715131. PMID 34790108 DOI: 10.3389/fninf.2021.715131 |
0.769 |
|
2019 |
Groden M, Weigand M, Triesch J, Jedlicka P, Cuntz H. A Model of Brain Folding Based on Strong Local and Weak Long-Range Connectivity Requirements. Cerebral Cortex (New York, N.Y. : 1991). PMID 31808811 DOI: 10.1093/Cercor/Bhz249 |
0.507 |
|
2018 |
Wijesinghe LP, Triesch J, Shi BE. Robot End Effector Tracking Using Predictive Multisensory Integration. Frontiers in Neurorobotics. 12: 66. PMID 30386227 DOI: 10.3389/Fnbot.2018.00066 |
0.344 |
|
2018 |
Klos C, Miner D, Triesch J. Bridging structure and function: A model of sequence learning and prediction in primary visual cortex. Plos Computational Biology. 14: e1006187. PMID 29870532 DOI: 10.1371/journal.pcbi.1006187 |
0.385 |
|
2017 |
Zhu Q, Triesch J, Shi BE. Joint Learning of Binocularly Driven Saccades and Vergence by Active Efficient Coding. Frontiers in Neurorobotics. 11: 58. PMID 29163121 DOI: 10.3389/Fnbot.2017.00058 |
0.34 |
|
2017 |
Rosenow F, van Alphen N, Becker A, Chiocchetti A, Deichmann R, Deller T, Freiman T, Freitag CM, Gehrig J, Hermsen AM, Jedlicka P, Kell C, Klein KM, Knake S, Kullmann DM, ... ... Triesch J, et al. Personalized translational epilepsy research - Novel approaches and future perspectives: Part I: Clinical and network analysis approaches. Epilepsy & Behavior : E&B. PMID 28917501 DOI: 10.1016/J.Yebeh.2017.06.041 |
0.542 |
|
2017 |
Bauer S, van Alphen N, Becker A, Chiocchetti A, Deichmann R, Deller T, Freiman T, Freitag CM, Gehrig J, Hermsen AM, Jedlicka P, Kell C, Klein KM, Knake S, Kullmann DM, ... ... Triesch J, et al. Personalized translational epilepsy research - Novel approaches and future perspectives: Part II: Experimental and translational approaches. Epilepsy & Behavior : E&B. PMID 28917498 DOI: 10.1016/J.Yebeh.2017.06.040 |
0.54 |
|
2017 |
Wang Q, Rothkopf CA, Triesch J. A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity. Plos Computational Biology. 13: e1005632. PMID 28767646 DOI: 10.1371/Journal.Pcbi.1005632 |
0.793 |
|
2017 |
Del Papa B, Priesemann V, Triesch J. Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network. Plos One. 12: e0178683. PMID 28552964 DOI: 10.1371/journal.pone.0178683 |
0.684 |
|
2016 |
Priamikov A, Fronius M, Shi B, Triesch J. OpenEyeSim: A biomechanical model for simulation of closed-loop visual perception. Journal of Vision. 16: 25. PMID 28006074 DOI: 10.1167/16.15.25 |
0.345 |
|
2016 |
Zhang C, Triesch J, Shi BE. An active-efficient-coding model of optokinetic nystagmus. Journal of Vision. 16: 10. PMID 27832268 DOI: 10.1167/16.14.10 |
0.351 |
|
2016 |
Sharpee TO, Destexhe A, Kawato M, Sekulić V, Skinner FK, Wójcik DK, Chintaluri C, Cserpán D, Somogyvári Z, Kim JK, Kilpatrick ZP, Bennett MR, Josić K, Elices I, Arroyo D, ... ... Triesch J, et al. 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54. PMID 27534393 DOI: 10.1186/S12868-016-0283-6 |
0.673 |
|
2015 |
Hartmann C, Miner DC, Triesch J. Precise Synaptic Efficacy Alignment Suggests Potentiation Dominated Learning. Frontiers in Neural Circuits. 9: 90. PMID 26793070 DOI: 10.3389/fncir.2015.00090 |
0.328 |
|
2015 |
Hartmann C, Lazar A, Nessler B, Triesch J. Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network. Plos Computational Biology. 11: e1004640. PMID 26714277 DOI: 10.1371/Journal.Pcbi.1004640 |
0.552 |
|
2015 |
Caligiore D, Mustile M, Cipriani D, Redgrave P, Triesch J, De Marsico M, Baldassarre G. Intrinsic motivations drive learning of eye movements: an experiment with human adults. Plos One. 10: e0118705. PMID 25775248 DOI: 10.1371/Journal.Pone.0118705 |
0.381 |
|
2015 |
Hartmann C, Lazar A, Triesch J. Key features of neural variability emerge from self-organized sequence learning in a deterministic neural network Bmc Neuroscience. 16: 266. DOI: 10.1186/1471-2202-16-S1-P266 |
0.535 |
|
2015 |
Miner D, Triesch J. Self-organization of complex cortex-like wiring in a spiking neural network model Bmc Neuroscience. 16: 265. DOI: 10.1186/1471-2202-16-S1-P265 |
0.308 |
|
2015 |
Teulière C, Forestier S, Lonini L, Zhang C, Zhao Y, Shi B, Triesch J. Self-calibrating smooth pursuit through active efficient coding Robotics and Autonomous Systems. 71: 3-12. DOI: 10.1016/J.Robot.2014.11.006 |
0.345 |
|
2014 |
Scocchia L, Valsecchi M, Triesch J. Top-down influences on ambiguous perception: the role of stable and transient states of the observer. Frontiers in Human Neuroscience. 8: 979. PMID 25538601 DOI: 10.3389/fnhum.2014.00979 |
0.307 |
|
2014 |
Priesemann V, Wibral M, Valderrama M, Pröpper R, Le Van Quyen M, Geisel T, Triesch J, Nikoli? D, Munk MH. Spike avalanches in vivo suggest a driven, slightly subcritical brain state. Frontiers in Systems Neuroscience. 8: 108. PMID 25009473 DOI: 10.3389/Fnsys.2014.00108 |
0.698 |
|
2014 |
Savin C, Triesch J. Emergence of task-dependent representations in working memory circuits. Frontiers in Computational Neuroscience. 8: 57. PMID 24904395 DOI: 10.3389/Fncom.2014.00057 |
0.6 |
|
2014 |
Krieg D, Triesch J. A unifying theory of synaptic long-term plasticity based on a sparse distribution of synaptic strength. Frontiers in Synaptic Neuroscience. 6: 3. PMID 24624080 DOI: 10.3389/fnsyn.2014.00003 |
0.306 |
|
2014 |
Deák GO, Krasno AM, Triesch J, Lewis J, Sepeta L. Watch the hands: infants can learn to follow gaze by seeing adults manipulate objects. Developmental Science. 17: 270-81. PMID 24387193 DOI: 10.1111/Desc.12122 |
0.657 |
|
2014 |
Lonini L, Dimitrakakis C, Rothkopf CA, Triesch J. Generalization and interference in human motor control Computational and Robotic Models of the Hierarchical Organization of Behavior. 155-176. DOI: 10.1007/978-3-642-39875-9_8 |
0.698 |
|
2013 |
Triesch J. Imitation learning based on an intrinsic motivation mechanism for efficient coding. Frontiers in Psychology. 4: 800. PMID 24204350 DOI: 10.3389/fpsyg.2013.00800 |
0.375 |
|
2013 |
Pamplona D, Triesch J, Rothkopf CA. Power spectra of the natural input to the visual system. Vision Research. 83: 66-75. PMID 23458676 DOI: 10.1016/J.Visres.2013.01.011 |
0.769 |
|
2013 |
Priesemann V, Wibral M, Triesch J. Learning more by sampling less: subsampling effects are model specific Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P414 |
0.336 |
|
2013 |
Wang Q, Bolhuis J, Rothkopf C, Kolling T, Knopf M, Triesch J. Infants in Control - Rapid Learning of Action Outcomes by 6 and 8-Month-Olds in a Gaze-Contingent Paradigm Journal of Vision. 13: 922-922. DOI: 10.1167/13.9.922 |
0.767 |
|
2013 |
Pamplona D, Triesch J, Rothkopf CA. Can the imaging process explain ganglion cells anisotropies Perception. 42: 144-144. DOI: 10.1068/V130730 |
0.741 |
|
2012 |
Wang Q, Bolhuis J, Rothkopf CA, Kolling T, Knopf M, Triesch J. Infants in control: rapid anticipation of action outcomes in a gaze-contingent paradigm. Plos One. 7: e30884. PMID 22363507 DOI: 10.1371/Journal.Pone.0030884 |
0.766 |
|
2012 |
Pamplona D, Triesch J, Rothkopf CA. The statistics of looking: Deriving properties of retinal ganglion cells across the visual field Journal of Vision. 12: 771-771. DOI: 10.1167/12.9.771 |
0.746 |
|
2012 |
Jasso H, Triesch J, Deák G, Lewis JM. A unified account of gaze following Ieee Transactions On Autonomous Mental Development. 4: 257-272. DOI: 10.1109/Tamd.2012.2208640 |
0.691 |
|
2012 |
Zhao Y, Rothkopf CA, Triesch J, Shi BE. A unified model of the joint development of disparity selectivity and vergence control 2012 Ieee International Conference On Development and Learning and Epigenetic Robotics, Icdl 2012. DOI: 10.1109/DevLrn.2012.6400876 |
0.713 |
|
2011 |
Saeb S, Weber C, Triesch J. Learning the optimal control of coordinated eye and head movements. Plos Computational Biology. 7: e1002253. PMID 22072953 DOI: 10.1371/Journal.Pcbi.1002253 |
0.781 |
|
2011 |
Weisswange TH, Rothkopf CA, Rodemann T, Triesch J. Bayesian cue integration as a developmental outcome of reward mediated learning. Plos One. 6: e21575. PMID 21750717 DOI: 10.1371/journal.pone.0021575 |
0.78 |
|
2011 |
Toutounji H, Rothkopf CA, Triesch J. Scalable reinforcement learning through hierarchical decompositions for weakly-coupled problems 2011 Ieee International Conference On Development and Learning, Icdl 2011. DOI: 10.1109/DEVLRN.2011.6037351 |
0.766 |
|
2011 |
Lazar A, Pipa G, Triesch J. Emerging Bayesian priors in a self-organizing recurrent network Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6792: 127-134. DOI: 10.1007/978-3-642-21738-8_17 |
0.637 |
|
2010 |
Simmering VR, Triesch J, Deák GO, Spencer JP. To Model or Not to Model? A Dialogue on the Role of Computational Modeling in Developmental Science. Child Development Perspectives. 4: 152-158. PMID 21625352 DOI: 10.1111/j.1750-8606.2010.00134.x |
0.62 |
|
2010 |
Franz A, Triesch J. A unified computational model of the development of object unity, object permanence, and occluded object trajectory perception. Infant Behavior & Development. 33: 635-53. PMID 20864178 DOI: 10.1016/j.infbeh.2010.07.018 |
0.499 |
|
2010 |
Savin C, Joshi P, Triesch J. Independent component analysis in spiking neurons. Plos Computational Biology. 6: e1000757. PMID 20421937 DOI: 10.1371/Journal.Pcbi.1000757 |
0.681 |
|
2010 |
Rothkopf C, Weisswange T, Triesch J. A walk through the woods explains the space variant oblique effect Journal of Vision. 9: 1049-1049. DOI: 10.1167/9.8.1049 |
0.729 |
|
2010 |
Robinson AE, Triesch J, Hayhoe MM, Droll JA, Sullivan BT. Change blindness during multiple interactions with a single object Journal of Vision. 6: 986-986. DOI: 10.1167/6.6.986 |
0.518 |
|
2010 |
Rothkopf C, Weisswange T, Triesch J. Computational modeling of multisensory object perception Multisensory Object Perception in the Primate Brain. 21-53. DOI: 10.1007/978-1-4419-5615-6_3 |
0.75 |
|
2009 |
Lazar A, Pipa G, Triesch J. SORN: a self-organizing recurrent neural network. Frontiers in Computational Neuroscience. 3: 23. PMID 19893759 DOI: 10.3389/Neuro.10.023.2009 |
0.697 |
|
2009 |
Saeb S, Weber C, Triesch J. Goal-directed learning of features and forward models. Neural Networks : the Official Journal of the International Neural Network Society. 22: 586-92. PMID 19616917 DOI: 10.1016/J.Neunet.2009.06.049 |
0.797 |
|
2009 |
Savin C, Triesch J, Meyer-Hermann M. Epileptogenesis due to glia-mediated synaptic scaling. Journal of the Royal Society, Interface / the Royal Society. 6: 655-68. PMID 18986963 DOI: 10.1098/Rsif.2008.0387 |
0.582 |
|
2009 |
Weber C, Triesch J. Implementations and implications of foveated vision Recent Patents On Computer Science. 2: 75-85. DOI: 10.2174/1874479600902010075 |
0.671 |
|
2009 |
Wibral M, Vicente R, Triesch J, Pipa G. Using transfer entropy to measure the patterns of information flow though cortex: application to MEG recordings from a visual Simon task Bmc Neuroscience. 10: P232. DOI: 10.1186/1471-2202-10-S1-P232 |
0.618 |
|
2009 |
Weber C, Triesch J. Goal-directed feature learning Proceedings of the International Joint Conference On Neural Networks. 3319-3326. DOI: 10.1109/IJCNN.2009.5179064 |
0.654 |
|
2009 |
Saeb S, Weber C, Triesch J. A neural model for the adaptive control of saccadic eye movements Proceedings of the International Joint Conference On Neural Networks. 2740-2747. DOI: 10.1109/IJCNN.2009.5178878 |
0.767 |
|
2009 |
Joshi P, Triesch J. Rules for information maximization in spiking neurons using intrinsic plasticity Proceedings of the International Joint Conference On Neural Networks. 1456-1461. DOI: 10.1109/IJCNN.2009.5178625 |
0.452 |
|
2009 |
Rothkopf CA, Weisswange TH, Triesch J. Learning independent causes in natural images explains the spacevariant oblique effect 2009 Ieee 8th International Conference On Development and Learning, Icdl 2009. DOI: 10.1109/DEVLRN.2009.5175534 |
0.77 |
|
2009 |
Weisswange TH, Rothkopf CA, Rodemanny T, Triesch J. Can reinforcement learning explain the development of causal inference in multisensory integration? 2009 Ieee 8th International Conference On Development and Learning, Icdl 2009. DOI: 10.1109/DEVLRN.2009.5175531 |
0.773 |
|
2009 |
Joshi P, Triesch J. Optimizing generic neural microcircuits through reward modulated STDP Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5768: 239-248. DOI: 10.1007/978-3-642-04274-4_25 |
0.464 |
|
2009 |
Gerhard F, Savin C, Triesch J. A robust biologically plausible implementation of ICA-like learning Esann 2009 Proceedings, 17th European Symposium On Artificial Neural Networks - Advances in Computational Intelligence and Learning. 147-152. |
0.743 |
|
2008 |
Weber C, Triesch J. A sparse generative model of V1 simple cells with intrinsic plasticity. Neural Computation. 20: 1261-84. PMID 18194109 DOI: 10.1162/Neco.2007.02-07-472 |
0.671 |
|
2008 |
Jasso H, Triesch J, Deák G. A reinforcement learning model of social referencing 2008 Ieee 7th International Conference On Development and Learning, Icdl. 286-291. DOI: 10.1109/DEVLRN.2008.4640844 |
0.638 |
|
2008 |
Kim H, Jasso H, Deák G, Triesch J. A robotic model of the development of gaze following 2008 Ieee 7th International Conference On Development and Learning, Icdl. 238-243. DOI: 10.1109/DEVLRN.2008.4640836 |
0.602 |
|
2008 |
Franz A, Triesch J. Modeling the development of causality and occlusion perception in infants 2008 Ieee 7th International Conference On Development and Learning, Icdl. 174-179. DOI: 10.1109/DEVLRN.2008.4640825 |
0.416 |
|
2008 |
Joshi P, Triesch J. A globally asymptotically stable plasticity rule for firing rate homeostasis Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5164: 567-576. DOI: 10.1007/978-3-540-87559-8_59 |
0.441 |
|
2008 |
Lazar A, Pipa G, Triesch J. Predictive coding in cortical microcircuits Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5164: 386-395. DOI: 10.1007/978-3-540-87559-8_40 |
0.617 |
|
2008 |
Weber C, Triesch J. From exploration to planning Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5163: 740-749. DOI: 10.1007/978-3-540-87536-9_76 |
0.574 |
|
2008 |
Willadsen K, Triesch J, Wiles J. Understanding robustness in random boolean networks Artificial Life Xi: Proceedings of the 11th International Conference On the Simulation and Synthesis of Living Systems, Alife 2008. 694-701. |
0.76 |
|
2007 |
Lazar A, Pipa G, Triesch J. Fading memory and time series prediction in recurrent networks with different forms of plasticity. Neural Networks : the Official Journal of the International Neural Network Society. 20: 312-22. PMID 17556114 DOI: 10.1016/J.Neunet.2007.04.020 |
0.689 |
|
2007 |
Triesch J, Jasso H, Deák GO. Emergence of mirror neurons in a model of gaze following Adaptive Behavior. 15: 149-165. DOI: 10.1177/1059712307078654 |
0.663 |
|
2007 |
Butko NJ, Triesch J. Learning sensory representations with intrinsic plasticity Neurocomputing. 70: 1130-1138. DOI: 10.1016/J.Neucom.2006.11.006 |
0.363 |
|
2006 |
Eckes C, Triesch J, von der Malsburg C. Analysis of cluttered scenes using an elastic matching approach for stereo images. Neural Computation. 18: 1441-71. PMID 16764510 DOI: 10.1162/neco.2006.18.6.1441 |
0.587 |
|
2006 |
Triesch J, Teuscher C, Deák GO, Carlson E. Gaze following: why (not) learn it? Developmental Science. 9: 125-47. PMID 16472311 DOI: 10.1111/J.1467-7687.2006.00470.X |
0.663 |
|
2006 |
Triesch J, Teuscher C, Deák GO. Response: Gaze following: How (not) to derive predictions from a computational model Developmental Science. 9: 156-157. DOI: 10.1111/J.1467-7687.2006.00474.X |
0.666 |
|
2005 |
Droll JA, Hayhoe MM, Triesch J, Sullivan BT. Task demands control acquisition and storage of visual information. Journal of Experimental Psychology. Human Perception and Performance. 31: 1416-38. PMID 16366799 DOI: 10.1037/0096-1523.31.6.1416 |
0.499 |
|
2004 |
Droll J, Hayhoe MM, Triesch J, Sullivan BT. Working memory for object features is influenced by scene context Journal of Vision. 4: 152-152. DOI: 10.1167/4.8.152 |
0.461 |
|
2003 |
Triesch J, Ballard DH, Hayhoe MM, Sullivan BT. What you see is what you need. Journal of Vision. 3: 86-94. PMID 12678628 DOI: 10:1167/3.1.9 |
0.704 |
|
2003 |
Droll JA, Hayhoe MM, Triesch J, Sullivan BT. Task relevance of object features modulates the content of visual working memory Journal of Vision. 3: 28a. DOI: 10.1167/3.9.28 |
0.48 |
|
2002 |
Triesch J, Ballard DH, Jacobs RA. Fast temporal dynamics of visual cue integration. Perception. 31: 421-34. PMID 12018788 DOI: 10.1167/1.3.463 |
0.639 |
|
2002 |
Triesch J, Sullivan BT, Hayhoe MM, Ballard DH. Transient visual representations: A change blindness approach Journal of Vision. 2: 244a. DOI: 10.1167/2.7.244 |
0.702 |
|
2002 |
Triesch J, Von der Malsburg C. Classification of hand postures against complex backgrounds using elastic graph matching Image and Vision Computing. 20: 937-943. DOI: 10.1016/S0262-8856(02)00100-2 |
0.502 |
|
2002 |
Hayhoe MM, Ballard DH, Triesch J, Shinoda H, Aivar P, Sullivan B. Vision in natural and virtual environments Eye Tracking Research and Applications Symposium (Etra). 7-13. |
0.71 |
|
2002 |
Triesch J, Sullivan BT, Hayhoe MM, Ballard DH. Saccade contingent updating in virtual reality Eye Tracking Research and Applications Symposium (Etra). 95-102. |
0.697 |
|
2001 |
Triesch J, von der Malsburg C. Democratic integration: self-organized integration of adaptive cues. Neural Computation. 13: 2049-74. PMID 11516357 DOI: 10.1162/089976601750399308 |
0.539 |
|
2001 |
Triesch J, Von Der Malsburg C. A system for person-independent hand posture recognition against complex backgrounds Ieee Transactions On Pattern Analysis and Machine Intelligence. 23: 1449-1453. DOI: 10.1109/34.977568 |
0.511 |
|
2000 |
Triesch J, Von Der Malsburg C. Self-organized integration of adaptive visual cues for face tracking Proceedings - 4th Ieee International Conference On Automatic Face and Gesture Recognition, Fg 2000. 102-107. DOI: 10.1109/AFGR.2000.840619 |
0.54 |
|
1999 |
Becker M, Kefalea E, Maël E, Von Der Malsburg C, Pagel M, Triesch J, Vorbrüggen JC, Würtz RP, Zadel S. GripSee: a gesture-controlled robot for object perception and manipulation Autonomous Robots. 6: 203-221. DOI: 10.1023/A:1008839628783 |
0.7 |
|
1999 |
Triesch J, Wieghardt J, Maël E, Von Der Malsburg C. Towards imitation learning of grasping movements by an autonomous robot Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1739: 73-84. DOI: 10.1007/3-540-46616-9_7 |
0.579 |
|
1998 |
Triesch J, Von Der Malsburg C. A gesture interface for human-robot-interaction Proceedings - 3rd Ieee International Conference On Automatic Face and Gesture Recognition, Fg 1998. 546-551. DOI: 10.1109/AFGR.1998.671005 |
0.51 |
|
1998 |
Triesch J, von der Malsburg C. Robotic gesture recognition Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1371: 233-244. DOI: 10.1007/BFb0053003 |
0.525 |
|
1996 |
Triesch J, Von Der Malsburg C. Binding- A proposed experiment and a model Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1112: 685-690. DOI: 10.1007/3-540-61510-5_116 |
0.513 |
|
1996 |
Triesch J, von der Malsburg C. Robust classification of hand postures against complex backgrounds Proceedings of the International Conference On Automatic Face and Gesture Recognition. 170-175. |
0.507 |
|
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