[robotics-worldwide] Visual Pattern Recognition / Neural Network ReNNaissance / Jobs in Vision-Based Robotics
juergen at idsia.ch
Sat Feb 5 08:07:49 PST 2011
Many future robots will depend on vision. Recently our neural computer
vision team collected a string of 1st ranks in the following visual
pattern recognition competitions and benchmarks:
1. Online Traffic Sign Recognition Competition, U. Bochum (1st & 2nd
rank; 1.02% error rate, January 2011).
2. NORB Object Recognition Benchmark, NYU, 2004. New record (2.53%
error rate) in January 2011 .
3. CIFAR-10 Object Recognition Benchmark, U. Toronto, 2009. New record
(19.51% error rate) in January 2011 .
4. MNIST Handwritten Digit Recognition Benchmark, NYU, 1998. New
record (0.35% error rate) in 2010, tied in January 2011 .
5.-7. Old news: Three Connected Handwriting Recognition Competitions
at ICDAR 2009, all won by multi-dimensional LSTM recurrent neural
None of 1-7 requires the traditional sophisticated computer vision
techniques developed over the past six decades or so. Instead, we use
supervised feedforward or recurrent neural networks with many non-
linear processing stages. GPUs speed up learning by a factor of up to
50. No need for unsupervised pre-training, which is a bit depressing,
as we have developed unsupervised learning algorithms for two
decades. Nevertheless, we think our results are contributing to a
second Neural Network ReNNaissance (the first one happened in the
1980s and early 90s). Most recent paper:
 D. C. Ciresan, U. Meier, J. Masci, L. M. Gambardella, J.
Schmidhuber. High-Performance Neural Networks for Visual Object
Classification. Preprint arXiv:1102.0183v1 [cs.AI], 1 Feb 2011.
Overview web site:
We are hiring postdocs and PhD students in
vision-based adaptive robotics and related fields:
Postdoc SFR 72,000/year ~ US$ 75,400/year as of 4/2/2011;
PhD student SFR 40,800/year ~ US$ 42,700/year:
BTW, Switzerland is the best country for scientists:
Director of the Swiss AI Lab IDSIA, Lugano
Professor of Artificial Intelligence, Univ. Lugano
Professor SUPSI, Manno-Lugano, Switzerland
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