TY  - CHAP
A1  - Walter, Peter
A1  - Elsen, Ingo
A1  - Müller, Holger
A1  - Kraiss, Karl-Friedrich
T1  - 3D object recognition with a specialized mixtures of experts architecture
T2  - IJCNN'99. International Joint Conference on Neural Networks. Proceedings
N2  - Aim of the AXON2 project (Adaptive Expert System for Object Recogniton using Neuml Networks) is the development of an object recognition system (ORS) capable of recognizing isolated 3d objects from arbitrary views. Commonly, classification is based on a single feature extracted from the original image. Here we present an architecture adapted from the Mixtures of Eaqerts algorithm which uses multiple neuml networks to integmte different features. During tmining each neural network specializes in a subset of objects or object views appropriate to the properties of the corresponding feature space. In recognition mode the system dynamically chooses the most relevant features and combines them with maximum eficiency. The remaining less relevant features arz not computed and do therefore not decelerate the-recognition process. Thus, the algorithm is well suited for ml-time applications.
Y1  - 1999
SN  - 0-7803-5529-6
U6  - http://dx.doi.org/10.1109/IJCNN.1999.836243
SN  - 1098-7576
N1  - Washington, DC 10-16.07.1999
SP  - 3563
EP  - 3568
PB  - IEEE
CY  - New York
ER  - 
TY  - CHAP
A1  - Altherr, Lena
A1  - Conzen, Max
A1  - Elsen, Ingo
A1  - Frauenrath, Tobias
A1  - Lyrmann, Andreas
ED  - Reiff-Stephan, Jörg
ED  - Jäkel, Jens
ED  - Schwarz, André
T1  - Sensor retrofitting of existing buildings in an interdisciplinary teaching project at university level
T2  - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel
N2  - Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems
KW  - Building Automation
KW  - Smart Building
KW  - CO2
KW  - Carbon Dioxide
KW  - Education
Y1  - 2023
SN  - 978-3-910103-01-6
U6  - http://dx.doi.org/10.33968/2023.04
N1  - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023.
BTS Connected Buildings & Cities Luxemburg
(Tagungsband unter https://doi.org/10.33968/2023.01)
SP  - 31
EP  - 40
PB  - le-tex publishing services GmbH
CY  - Leipzig
ER  -