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
Dalam makalah ini, kami meneroka kemungkinan menggunakan ingatan bersekutu untuk mengesan pandangan hadapan muka manusia dalam adegan yang kompleks. Sifat menarik sistem pengesanan muka berasaskan ingatan bersekutu ialah pembelajaran ingatan bersekutu boleh dicapai dengan menggunakan peraturan pembelajaran Hebbian yang mudah. Di samping itu, peraturan heuristik mudah digunakan untuk menapis sejumlah imej bukan muka dengan pantas pada permulaan keseluruhan prosedur pengesanan. Dengan menggunakan peraturan, kami tidak akan membuang sumber pengiraan yang tidak perlu pada imej bukan muka tersebut. Pangkalan data yang terdiri daripada 74 imej telah digunakan untuk menguji prestasi sistem pengesanan muka manusia berasaskan ingatan bersekutu kami.
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Salinan
Mu-Chun SU, Chien-Hsing CHOU, "Associative-Memory-Based Human Face Detection" in IEICE TRANSACTIONS on Information,
vol. E84-D, no. 8, pp. 1067-1074, August 2001, doi: .
Abstract: In this paper, we explore the possibility of applying associative memories for locating frontal views of human faces in complex scenes. An appealing property of the associative-memory-based face detection system is that learning of the associative memory may be achieved by using a simple Hebbian learning rule. In addition, a simple heuristic rule is used to quickly filter a certain amount of nonface images at the very beginning of the whole detection procedure. By using the rule, we won't waste unnecessary computational resources on those nonface images. A database consisting of 74 images was used to test the performance of our associative-memory-based human face detection system.
URL: https://global.ieice.org/en_transactions/information/10.1587/e84-d_8_1067/_p
Salinan
@ARTICLE{e84-d_8_1067,
author={Mu-Chun SU, Chien-Hsing CHOU, },
journal={IEICE TRANSACTIONS on Information},
title={Associative-Memory-Based Human Face Detection},
year={2001},
volume={E84-D},
number={8},
pages={1067-1074},
abstract={In this paper, we explore the possibility of applying associative memories for locating frontal views of human faces in complex scenes. An appealing property of the associative-memory-based face detection system is that learning of the associative memory may be achieved by using a simple Hebbian learning rule. In addition, a simple heuristic rule is used to quickly filter a certain amount of nonface images at the very beginning of the whole detection procedure. By using the rule, we won't waste unnecessary computational resources on those nonface images. A database consisting of 74 images was used to test the performance of our associative-memory-based human face detection system.},
keywords={},
doi={},
ISSN={},
month={August},}
Salinan
TY - JOUR
TI - Associative-Memory-Based Human Face Detection
T2 - IEICE TRANSACTIONS on Information
SP - 1067
EP - 1074
AU - Mu-Chun SU
AU - Chien-Hsing CHOU
PY - 2001
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E84-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2001
AB - In this paper, we explore the possibility of applying associative memories for locating frontal views of human faces in complex scenes. An appealing property of the associative-memory-based face detection system is that learning of the associative memory may be achieved by using a simple Hebbian learning rule. In addition, a simple heuristic rule is used to quickly filter a certain amount of nonface images at the very beginning of the whole detection procedure. By using the rule, we won't waste unnecessary computational resources on those nonface images. A database consisting of 74 images was used to test the performance of our associative-memory-based human face detection system.
ER -