메뉴 건너뛰기




Volumn 20, Issue 8, 2007, Pages 904-916

Interpolating vectors for robust pattern recognition

Author keywords

Interpolating vector; Labeled competitive learning; Neocognitron; Pattern recognition

Indexed keywords

ALGORITHMS; ERROR ANALYSIS; INTERPOLATION; LEARNING SYSTEMS; ROBUST CONTROL;

EID: 34848866307     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2007.06.003     Document Type: Article
Times cited : (14)

References (11)
  • 1
    • 27144489164 scopus 로고    scopus 로고
    • A tutorial on support vector machines for pattern recognition
    • Burges C. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery 2 (1998) 1-47
    • (1998) Data Mining and Knowledge Discovery , vol.2 , pp. 1-47
    • Burges, C.1
  • 3
    • 0019152630 scopus 로고
    • Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position
    • Fukushima K. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biological Cybernetics 36 4 (1980) 193-202
    • (1980) Biological Cybernetics , vol.36 , Issue.4 , pp. 193-202
    • Fukushima, K.1
  • 4
    • 0023846591 scopus 로고
    • Neocognitron: A hierarchical neural network capable of visual pattern recognition
    • Fukushima K. Neocognitron: A hierarchical neural network capable of visual pattern recognition. Neural Networks 1 2 (1988) 119-130
    • (1988) Neural Networks , vol.1 , Issue.2 , pp. 119-130
    • Fukushima, K.1
  • 5
    • 0037381347 scopus 로고    scopus 로고
    • Neocognitron for handwritten digit recognition
    • A computer program of this neocognitron in C language is available from Visiome Platform: http://platform.visiome.neuroinf.jp/.
    • Fukushima K. Neocognitron for handwritten digit recognition. Neurocomputing 51 (2003) 161-180. A computer program of this neocognitron in C language is available from Visiome Platform: http://platform.visiome.neuroinf.jp/.
    • (2003) Neurocomputing , vol.51 , pp. 161-180
    • Fukushima, K.1
  • 6
    • 0030152250 scopus 로고    scopus 로고
    • Use of different thresholds in learning and recognition
    • Fukushima K., and Tanigawa M. Use of different thresholds in learning and recognition. Neurocomputing 11 1 (1996) 1-17
    • (1996) Neurocomputing , vol.11 , Issue.1 , pp. 1-17
    • Fukushima, K.1    Tanigawa, M.2
  • 7
    • 0021412027 scopus 로고
    • Vector quantization
    • Gray R.M. Vector quantization. IEEE ASSP Magazine 1 2 (1984) 4-29
    • (1984) IEEE ASSP Magazine , vol.1 , Issue.2 , pp. 4-29
    • Gray, R.M.1
  • 8
    • 33645410496 scopus 로고
    • Receptive fields, binocular interaction and functional architecture in the cat's visual cortex
    • Hubel D.H., and Wiesel T.N. Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. Journal of Physiology (Cambridge, Eng.) 106 1 (1962) 106-154
    • (1962) Journal of Physiology (Cambridge, Eng.) , vol.106 , Issue.1 , pp. 106-154
    • Hubel, D.H.1    Wiesel, T.N.2
  • 9
    • 78651178699 scopus 로고
    • Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat
    • Hubel D.H., and Wiesel T.N. Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. Journal of Neurophysiology 28 2 (1965) 229-289
    • (1965) Journal of Neurophysiology , vol.28 , Issue.2 , pp. 229-289
    • Hubel, D.H.1    Wiesel, T.N.2
  • 10
    • 0003410791 scopus 로고
    • Springer-Verlag, Berlin, Heidelberg, New York
    • Kohonen T. The self-organizing maps (1995), Springer-Verlag, Berlin, Heidelberg, New York
    • (1995) The self-organizing maps
    • Kohonen, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.