TY  - JOUR
A1  - Lechner, Werner
T1  - Face recogniton based on the optimal combination of neural networks, eigenfaces and least squares matching methods
N2  - Report of a research project of the Fachhochschule Hannover, University of Applied Sciences and Arts, Department of Information Technologies. Automatic face recognition increases the security standards at public places and border checkpoints. The picture inside the identification documents could widely differ from the face, that is scanned under random lighting conditions and for unknown poses. The paper describes an optimal combination of three key algorithms of object recognition, that are able to perform in real time. The camera scan is processed by a recurrent neural network, by a Eigenfaces (PCA) method and by a least squares matching algorithm. Several examples demonstrate the achieved robustness and high recognition rate.
KW  - Biometrie
KW  - Neuronales Netz
KW  - Künstliche Intelligenz
KW  - Gesichtserkennung
KW  - face recognition
KW  - eigenface
Y1  - 2008
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:960-opus-470
ER  - 
TY  - RPRT
A1  - Lechner, Werner
T1  - Aufbau eines mobilen Systems zur Erkennung von Gesichtern durch die optimale Kombination neuronaler Netze mit Eigenwert- und Matching-Methoden
N2  - Die computergestützte Erkennung von Personen basiert auf der quantitativen Feststellung einer möglichst weitgehenden Übereinstimmung zwischen einer gespeicherten Graphik und dem momentan erfassten Kamerabild. Der vorliegende Forschungsbericht beschreibt ein solches Erkennungssystem, das auf der optimalen Kombination unterschiedlicher, sich gegenseitig ergänzender Erkennungsverfahren beruht. Im Zentrum des Erkennungssystems arbeitet als wesentliche Komponente ein neuronales Netz.
KW  - Biometrie
KW  - Neuronales Netz
KW  - Künstliche Intelligenz
KW  - artificial intelligence
KW  - neuronal networks
Y1  - 2008
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:960-opus-298
ER  - 
TY  - CHAP
A1  - Lechner, Werner
A1  - Müller, Frank
T1  - Intelligent Control of Autonomous Six-Legged Robots by Neural Networks
N2  - Autonomous mobile six-legged robots are able to demonstrate the potential of intelligent control systems based on recurrent neural networks. The robots evaluate only two forward and two backward looking infrared sensor signals. Fast converging genetic training algorithms are applied to train the robots to move straight in six directions. The robots performed successfully within an obstacle environment and there could be observed a never trained useful interaction between each of the single robots. The paper describes the robot systems and presents the test results. Video clips are downloadable under www.inform.fh-hannover.de/download/lechner.php. Held on IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003, April 2003, Portugal).
KW  - Künstliche Intelligenz
KW  - Robotik
KW  - Neuronales Netz
KW  - Genetischer Algorithmus
KW  - Intelligent control
KW  - Articial intelligence
KW  - Neural networks
KW  - Neural controls
KW  - Neural-network models
KW  - Robotics
KW  - Genetic algorithms
Y1  - 2008
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bsz:960-opus-289
ER  -