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In visual surface inspection application, the problem often faced is the collection an labelling of training material. The manual labelling of training samples requires much effort and is error prone since the defect classes may appear diffucult to discriminate even for a human. Frequent changes in the inspected material or imaging conditions may lead to unpractical often repeating training material collection cycles.

The SOM-based approach supports the labelling of training data, simplifies the retraining for changing material or imaging conditions, provides an intuative user's interface, and is computationally attractive for real-time applications.

G-SOM features

MVG/Downloads/Gsom (last edited 2011-11-22 12:19:26 by WebMaster)