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We are delighted to present the proceedings of DAGM 2004, and wish
to - press our gratitude to the many people whose e?orts made the
success of the conference possible. We received 146 contributions
of which we were able to - cept 22 as oral presentations and 48 as
posters. Each paper received 3 reviews, upon which decisions were
based. We are grateful for the dedicated work of the 38 members of
the program committee and the numerous referees. The careful review
process led to the exciting program which we are able to present in
this volume. Among the highlights of the meeting were the talks of
our four invited spe- ers, renowned experts in areas spanning
learning in theory, in vision and in robotics: - William T.
Freeman, Arti?cial Intelligence Laboratory, MIT: Sharing F- tures
for Multi-class Object Detection -
PietroPerona,Caltech:TowardsUnsupervisedLearningofObjectCategories
- StefanSchaal,DepartmentofComputerScience,UniversityofSouthernC-
ifornia: Real-Time Statistical Learning for Humanoid Robotics -
Vladimir Vapnik, NEC Research Institute: Empirical Inference
WearegratefulforeconomicsupportfromHondaResearchInstituteEurope,
ABW GmbH, Transtec AG, DaimlerChrysler, and Stemmer Imaging GmbH,
which enabled us to ? nance best paper prizes and a limited number
of travel grants. Many thanks to our local support Sabrina
Nielebock and Dagmar Maier, who dealt with the unimaginably diverse
range of practical tasks involved in planning a DAGM symposium.
Thanks to Richard van de Stadt for providing excellent software and
support for handling the reviewing process. A special thanks goes
to Jeremy Hill, who wrote and maintained the conference website.
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