$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

Evolving spiking neural networks for audiovisual information processing

Neural networks : the official journal of the International Neural Network Society, v.23 no.7, 2010년, pp.819 - 835  

Wysoski, S.G. (Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, 1051 Auckland, New Zealand) ,  Benuskova, L. ,  Kasabov, N.

Abstract AI-Helper 아이콘AI-Helper

This paper presents a new modular and integrative sensory information system inspired by the way the brain performs information processing, in particular, pattern recognition. Spiking neural networks are used to model human-like visual and auditory pathways. This bimodal system is trained to perform...

주제어

참고문헌 (73)

  1. Abeles 1982 Local cortical circuits: an electrophysiological study 

  2. Journal of Neuroscience Methods Abeles 107 141 2001 10.1016/S0165-0270(01)00364-8 Detecting precise firing sequences in experimental data 

  3. Network: Computation in Neural systems Bienenstock 6 179 1995 10.1088/0954-898X/6/2/004 A model of neocortex 

  4. EURASIP Journal on Applied Signal Processing Bimbot 4 430 2004 10.1155/S1110865704310024 A tutorial on text-independent speaker verification 

  5. IEEE Transactions on Pattern Analysis and Machine Intelligence Brunelli 17 10 955 1995 10.1109/34.464560 Person identification using multiple cues 

  6. International Journal of Speech Technology Burileanu 5 247 2002 10.1023/A:1020244924468 On performance improvement of a speaker verification system using vector quantization, cohorts and hybrid cohort-world models 

  7. Cerebral Cortex Calvert 11 1110 2001 10.1093/cercor/11.12.1110 Crossmodal processing in the human brain: insights from functional neuroimaging studies 

  8. Chevallier, S., Paugam-Moisy, H., & Lemaitre, F. (2005). Distributed processing for modelling real-time multimodal perception in a virtual robot. In International multi-conference parallel and distributed computing and networks (pp. 393-398). 

  9. IEEE Transactions on Systems, Man and Cybernetics, Part B Chibelushi 29 6 902 1999 10.1109/3477.809043 Adaptive classifier integration for robust pattern recognition 

  10. IEEE Transactions on Multimedia Chibelushi 4 1 23 2002 10.1109/6046.985551 A review of speech-based bimodal recognition 

  11. Crepet, A., Paugam-Moisy, H., Reynaud, E., & Puzenat, D. (2000). A modular neural model for binding several modalities. In International conference on artificial intelligence (pp. 921-928). 

  12. Neurocomputing Delorme 26-27 989 1999 10.1016/S0925-2312(99)00095-8 SpikeNet: a simulator for modeling large networks of integrate and fire neurons 

  13. Neurocomputing Delorme 38 2001 Networks of integrate-and-fire neurons using Rank Order Coding 

  14. Neural Networks Delorme 14 795 2001 10.1016/S0893-6080(01)00049-1 Face identification using one spike per neuron: resistance to image degradation 

  15. British Journal of Psychology Ellis 88 143 1997 10.1111/j.2044-8295.1997.tb02625.x Intra- and inter-modal repetition priming of familiar faces and voices 

  16. Behavioural Processes Eriksson 73 358 2006 10.1016/j.beproc.2006.08.005 Learning of auditory equivalence classes for vowels by rats 

  17. 10.1109/IJCNN.2006.246727 Eriksson, J. L., & Villa, A. E. P. (2006b). Artificial neural networks simulation of learning of auditory equivalence classes for vowels. In International joint conference on neural networks (pp. 1253-1260). 

  18. Fukushima 267 1982 Competition and cooperation in neural nets Neocognitron: a self-organizing neural network model for a mechanism of visual pattern recognition 

  19. Gallant 1995 Neural network learning and expert systems 

  20. Ganchev, T. (2005). Speaker recognition. Ph.D. thesis. Dept. of Electrical and Computer Engineering, University of Patras, Greece. 

  21. Gerstner 2002 Spiking neuron models 

  22. Journal of Neuroscience Ghazanfar 25 5004 2005 10.1523/JNEUROSCI.0799-05.2005 Multisensory integration of dynamic faces and voices in rhesus monkey auditory cortex 

  23. Journal of Phonetics Ghitza 16 109 1988 10.1016/S0095-4470(19)30469-3 Temporal non-place information in the auditory-nerve firing patterns as a front-end for speech recognition in a noisy environment 

  24. IEEE ASSP Magazine Gray 4 1984 10.1109/MASSP.1984.1162229 Vector quantization 

  25. Nature Neuroscience Gutig 9 420 2006 10.1038/nn1643 The tempotron: a neuron that learns spike timing-based decisions 

  26. 10.21437/Interspeech.2005-480 Holmberg, M., Gelbart, D., Ramacher, U., & Hemmert, W. (2005). Automatic speech recognition with neural spike trains. In Interspeech (pp. 1253-1256). 

  27. Nature Hopfield 376 6535 33 1995 10.1038/376033a0 Pattern recognition computation using action potential timing for stimulus representation 

  28. Journal of Physiology Hubel 160 106 1962 10.1113/jphysiol.1962.sp006837 Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex 

  29. Iwasa Vol. 4669 748 2007 ICANN Separation and recognition of multiple sound source using pulsed neuron model 

  30. Neural Computation Izhikevich 18 2 245 2006 10.1162/089976606775093882 Polychronization: computation with spikes 

  31. Kasabov 2007 Evolving connectionist systems 

  32. Kiang 1965 Discharge patterns of single fibers in the cat’s auditory nerve 

  33. IEEE Transactions on Pattern Analysis and Machine Intelligence Kittler 20 3 226 1998 10.1109/34.667881 On combining classifiers 

  34. PLoS Biology von Kriegstein 4 10 1809 2006 10.1371/journal.pbio.0040326 Implicit multisensory associations influence voice recognition 

  35. Journal of Cognitive Neuroscience von Kriegstein 17 3 367 2005 10.1162/0898929053279577 Interaction of face and voice areas during speaker recognition 

  36. Interdisciplinary Journal of Artificial Intelligence and the Simulation of Behaviour, AISB Kruger 15 417 2004 Biologically motivated multi-modal processing of visual primitives 

  37. Transactions of IEICE Kuroyanagi E77-D 4 466 1994 Auditory pulse neural network model to extract the inter-aural time and level difference for sound localization 

  38. 10.1109/IJCNN.2005.1556220 Loiselle, S., Rouat, J., Pressnitzer, D., & Thorpe, S. (2005). Exploration of Rank Order Coding with spiking neural networks for speech recognition. In International joint conference on neural networks (pp. 2076-2080). 

  39. Maciokas, J., Goodman, P. H., & Harris, F. C. Jr. (2002). Large-scale spike-timing dependent-plasticity model of bimodal (audio/visual) processing. In Technical report of brain computation laboratory. University of Nevada, Reno. 

  40. 10.1109/ICONIP.2002.1198140 Matsugu, M., Mori, K., Ishii, M., & Mitarai, Y. (2002). Convolutional spiking neural network model for robust face detection. In International conference on neural information processing (pp. 660-664). 

  41. Neural Networks Matsugu 16 555 2003 10.1016/S0893-6080(03)00115-1 Subject independent facial expression recognition with robust face detection using a convolutional neural network 

  42. Nature Neuroscience Mazurek 5 463 2002 10.1038/nn836 Limits to the temporal fidelity of cortical spike rate signals 

  43. McLennan, S., & Hockema, S. (2001). Spike-V: an adaptive mechanism for speech-rate independent timing. IULC working papers online 02-01. 

  44. Neural Computation Mel 9 777 1998 10.1162/neco.1997.9.4.777 SEEMORE: Combining colour, shape, and texture histogramming in a neurally-inspired approach to visual object recognition 

  45. Mercier, D., & Seguier, R. (2002). Spiking neurons (STANNs) in speech recognition. In 3rd WSES international conference on neural networks and applications. 

  46. Movellan Vol. 7 851 1995 Visual speech recognition with stochastic networks 

  47. Mozayyani, N., Baig, A.R., & Vaucher, G. (1998). A fully neural solution for on-line handwritten character recognition. In International joint conference on neural networks (pp. 160-164). 

  48. Network: Computation in Neural Systems Natschlager 9 3 319 1998 10.1088/0954-898X/9/3/003 Spatial and temporal pattern analysis via spiking neurons 

  49. Neurocomputing Natschlager 26-27 463 1999 10.1016/S0925-2312(99)00052-1 Pattern analysis with spiking neurons using delay coding 

  50. European Symposium on Artificial Neural Networks Perrinet 313 2002 Sparse image coding using an asynchronous spiking neural network 

  51. Science Poggio 247 978 1990 10.1126/science.247.4945.978 Regularization algorithms for learning that are equivalent to multilayer networks 

  52. Rabiner 1993 Fundamentals of speech recognition 

  53. Reece 2001 Pulsed neural networks Encoding information in neuronal activity 

  54. Digital Signal Processing Reynolds 10 19 2000 10.1006/dspr.1999.0361 Speaker verification using adapted Gaussian mixture models 

  55. Nature Neuroscience Riesenhuber 2 11 1019 1999 10.1038/14819 Hierarchical models of object recognition in cortex 

  56. Journal of the Acoustical Society of America Robert 106 4 1852 1999 10.1121/1.427935 A composite model of the auditory periphery for simulating responses to complex sounds 

  57. Computer Speech and Language Rosenberg 2 3-4 143 1987 10.1016/0885-2308(87)90005-2 Evaluation of a vector quantization talker recognition system in text independent and text dependent modes 

  58. Rouat Vol. 3445 317 2005 Nonlinear speech modelling Perceptive, non-linear speech processing and spiking neural networks 

  59. Digital Signal Processing Sanderson 14 449 2002 10.1016/j.dsp.2004.05.001 Identity verification using speech and face information 

  60. Seguier, R., & Mercier, D. (2001). A generic pretreatment for spiking neuron. Application on lipreading with STANN (Spatio-Temporal Artificial Neural Networks). In 5th international conference on artificial neural networks and genetic algorithms. 

  61. IEEE Transactions on Pattern Analysis and Machine Intelligence Serre 29 3 411 2007 10.1109/TPAMI.2007.56 Robust object recognition with cortex-like mechanisms 

  62. Journal of the Acoustical Society of America Shamma 78 1612 1986 10.1121/1.392799 A biophysical model of cochlear processing: intensity dependence of pure tone responses 

  63. Stein 1993 The merging of the senses 

  64. Nature Thorpe 381 520 1996 10.1038/381520a0 Speed of processing in the human visual system 

  65. Journal of Electrical Engineering Tikovic 52 3-4 68 2001 Implementation of a learning synapse and a neuron for pulse-coupled neural networks 

  66. Biosystems Vaucher 48 241 1998 10.1016/S0303-2647(98)00077-X An algebraic interpretation of PSP composition 

  67. 10.1109/CVPR.2001.990517 Viola, P., & Jones, M. J. (2001). Rapid object detection using a boosted cascade of simple features. In Proceedings of IEEE computer society conference on computer vision and pattern recognition, Vol. 1 (pp. 511-518). 

  68. Wysoski Vol. 4131 61 2006 ICANN On-line learning with structural adaptation in a network of spiking neurons for visual pattern recognition 

  69. Wysoski Vol. 4669 758 2007 ICANN Text-independent speaker authentication with spiking neural networks 

  70. Neurocomputing Wysoski 71 13-15 2563 2008 10.1016/j.neucom.2007.12.038 Fast and adaptive network of spiking neurons for multi-view visual pattern recognition 

  71. Wysoski vol. 4985 406 2008 ICONIP Adaptive spiking neural networks for audiovisual pattern recognition 

  72. Neural Networks Yamauchi 12 10 1347 1999 10.1016/S0893-6080(99)00064-7 A self-supervised learning system for pattern recognition by sensory integration 

  73. International Journal of Knowledge-Based and Intelligent Engineering Systems Yamauchi 5 3 142 2001 Sensory integrating neural network with selective attention architecture for autonomous robots 

관련 콘텐츠

저작권 관리 안내
섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로