@article{HoffschmidtPitzPaalBoehmer1999,
  author    = {Hoffschmidt, Bernhard and Pitz-Paal, Robert and B{\"o}hmer, M.},
  title     = {A new closed/open volumetric receiver concept for parabolictrough collectors (test results)},
  series = {Journal de physique. 9 (1999), H. 3},
  journal   = {Journal de physique. 9 (1999), H. 3},
  isbn      = {1155-4339},
  pages     = {3},
  year      = {1999},
  language  = {en}
}
@article{Harder1999,
  author    = {Harder, J{\"o}rn},
  title     = {A crystallographic model for the study of local deformation processes in polycrystals},
  series = {International journal of plasticity. 15 (1999), H. 6},
  journal   = {International journal of plasticity. 15 (1999), H. 6},
  isbn      = {0749-6419},
  pages     = {605 -- 624},
  year      = {1999},
  language  = {en}
}
@misc{Fabo1999,
  author    = {Fabo, Sabine},
  title     = {[Buchbesprechung] Yvonne Spielmann: Intermedialit{\"a}t - das System Peter Greenaway},
  series = {Kunstforum international. 148 (1999)},
  journal   = {Kunstforum international. 148 (1999)},
  isbn      = {0177-3674},
  pages     = {476 -- 477},
  year      = {1999},
  language  = {de}
}
@inproceedings{WalterElsenMuelleretal.1999,
  author    = {Walter, Peter and Elsen, Ingo and M{\"u}ller, Holger and Kraiss, Karl-Friedrich},
  title     = {3D object recognition with a specialized mixtures of experts architecture},
  series = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings},
  booktitle = {IJCNN'99. International Joint Conference on Neural Networks. Proceedings},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {0-7803-5529-6},
  issn      = {1098-7576},
  doi       = {10.1109/IJCNN.1999.836243},
  pages     = {3563 -- 3568},
  year      = {1999},
  abstract  = {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.},
  language  = {en}
}
@book{JanzEblingGottschalketal.1999,
  author    = {Janz, Norbert and Ebling, G{\"u}nther and Gottschalk, Sandra and Niggemann, Hiltrud},
  title     = {2nd Community Innovation Survey. Final Report. Report prepared for Eurostat / Ebling, G. , S. Gottschalk, N. Janz und H. Niggemann},
  publisher = {ZEW Zentrum f{\"u}r Europ{\"a}ische Wirtschaftsforschung},
  address   = {Mannheim},
  year      = {1999},
  language  = {en}
}
@book{JanzEblingGottschalketal.1999,
  author    = {Janz, Norbert and Ebling, G{\"u}nther and Gottschalk, Sandra and Niggemann, Hiltrud},
  title     = {2nd Community Innovation Survey. 2nd Interim Report. Report prepared for Eurostat / Ebling, G. , S. Gottschalk, N. Janz und H. Niggemann},
  publisher = {ZEW Zentrum f{\"u}r Europ{\"a}ische Wirtschaftsforschung},
  address   = {Mannheim},
  year      = {1999},
  language  = {en}
}