Pattern recognition in high energy physics with neural networks

Artificial neural networks (ANN) are introduced in the context of analyzing particle physics data. The power of these techniques are demonstrated in applications ranging from off-line jet identification to tracking. Among other things very successful results are presented for b-quark identification using hadronic information only. Also a novel approach for tracking using deformable templates is shown.

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