The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kaedah bentuk daripada fokus konvensional (SFF) mempunyai ketidaktepatan kerana penghampiran berterusan sekeping bagi permukaan imej terfokus (FIS). Kami mencadangkan skim yang lebih tepat untuk SFF berdasarkan perwakilan FIS tiga dimensi dari segi berat rangkaian saraf. Rangkaian saraf dilatih untuk mempelajari bentuk FIS yang memaksimumkan ukuran fokus.
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Salinan
Muhammad ASIF, Tae-Sun CHOI, "Shape from Focus Using Multilayer Feedforward Neural Networks" in IEICE TRANSACTIONS on Information,
vol. E83-D, no. 4, pp. 946-949, April 2000, doi: .
Abstract: The conventional shape from focus (SFF) methods have inaccuracies because of piecewise constant approximation of the focused image surface (FIS). We propose a more accurate scheme for SFF based on representation of three-dimensional FIS in terms of neural network weights. The neural networks are trained to learn the shape of the FIS that maximizes the focus measure.
URL: https://global.ieice.org/en_transactions/information/10.1587/e83-d_4_946/_p
Salinan
@ARTICLE{e83-d_4_946,
author={Muhammad ASIF, Tae-Sun CHOI, },
journal={IEICE TRANSACTIONS on Information},
title={Shape from Focus Using Multilayer Feedforward Neural Networks},
year={2000},
volume={E83-D},
number={4},
pages={946-949},
abstract={The conventional shape from focus (SFF) methods have inaccuracies because of piecewise constant approximation of the focused image surface (FIS). We propose a more accurate scheme for SFF based on representation of three-dimensional FIS in terms of neural network weights. The neural networks are trained to learn the shape of the FIS that maximizes the focus measure.},
keywords={},
doi={},
ISSN={},
month={April},}
Salinan
TY - JOUR
TI - Shape from Focus Using Multilayer Feedforward Neural Networks
T2 - IEICE TRANSACTIONS on Information
SP - 946
EP - 949
AU - Muhammad ASIF
AU - Tae-Sun CHOI
PY - 2000
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E83-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2000
AB - The conventional shape from focus (SFF) methods have inaccuracies because of piecewise constant approximation of the focused image surface (FIS). We propose a more accurate scheme for SFF based on representation of three-dimensional FIS in terms of neural network weights. The neural networks are trained to learn the shape of the FIS that maximizes the focus measure.
ER -