Four-layer neural network model of the equivalent luminous-efficiency function in the human vision

Jing Long Wu, Hajime Kita, Yoshikazu Nishikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a model of the equivalent luminous-efficency function based on the brightness perception which covers the scotopic, the mesopic and the photopic conditions. This function depends on the equivalent scotopic and the equivalent photopic luminous-efficiency functions, and depends also on the scotopic and the photopic coefficient functions. In order to describe the equivalent luminous-efficiency function, we construct a four-layer neural network. The network is composed of three parts: an input layer, hidden layers (hidden layer 1 and 2) and an output layer. This network is trained by the back-propagation learning algorithm with use of training data obtained by psychological experiments. After completion of learning, the response functions of the hidden units and the generalization capability of the network are examined. The response functions of the two hidden units express the scotopic and the photopic coefficients functions which depend nonlinearly on the input light-intensity level.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherPubl by IEEE
Pages207-210
Number of pages4
ISBN (Print)0780314212, 9780780314214
Publication statusPublished - Dec 1 1993
Externally publishedYes
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3) - Nagoya, Jpn
Duration: Oct 25 1993Oct 29 1993

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume1

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 1 (of 3)
CityNagoya, Jpn
Period10/25/9310/29/93

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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  • Cite this

    Wu, J. L., Kita, H., & Nishikawa, Y. (1993). Four-layer neural network model of the equivalent luminous-efficiency function in the human vision. In Proceedings of the International Joint Conference on Neural Networks (pp. 207-210). (Proceedings of the International Joint Conference on Neural Networks; Vol. 1). Publ by IEEE.