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 - JOUR A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich A1 - Krumbiegel, Dirk A1 - Walter, Peter A1 - Wickel, Jochen T1 - Visual information retrieval for 3D product identification: a midterm report JF - KI - Künstliche Intelligenz Y1 - 1999 SN - 1610-1987 SN - 0933-1875 VL - 13 IS - 1 SP - 64 EP - 67 PB - Springer CY - Berlin ER - TY - CHAP A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich A1 - Krumbiegel, Dirk T1 - Pixel based 3D object recognition with bidirectional associative memories T2 - International Conference on Neural Networks 1997 N2 - This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand. Y1 - 1997 SN - 0-7803-4122-8 N1 - June 9 - 12, 1997, Westin Galleria Hotel Houston, Texas, USA. SP - 1679 EP - 1684 PB - IEEE CY - New York ER - TY - JOUR A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich T1 - System concept and realization of a scalable neurocomputing architecture JF - Systems Analysis Modelling Simulation N2 - This paper describes the realization of a novel neurocomputer which is based on the concepts of a coprocessor. In contrast to existing neurocomputers the main interest was the realization of a scalable, flexible system, which is capable of computing neural networks of arbitrary topology and scale, with full independence of special hardware from the software's point of view. On the other hand, computational power should be added, whenever needed and flexibly adapted to the requirements of the application. Hardware independence is achieved by a run time system which is capable of using all available computing power, including multiple host CPUs and an arbitrary number of neural coprocessors autonomously. The realization of arbitrary neural topologies is provided through the implementation of the elementary operations which can be found in most neural topologies. Y1 - 1999 SN - 0232-9298 SN - 1029-4902 VL - 35 IS - 4 SP - 399 EP - 419 PB - Gordon and Breach Science Publishers CY - Amsterdam ER -