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Updated: Jul 14, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
Published on: February 15, 2017
Combining reconstruction and discrimination with class-specific sparse coding
Stephan Hasler1, Heiko Wersing, Edgar Körner
1Honda Research Institute Europe GmbH, Offenbach/Main, Germany. Stephan.hasler@honda-ri.de
Abstract:
Sparse coding is an important approach for the unsupervised learning of sensory features. In this contribution, we present two new methods that extend the traditional sparse coding approach with supervised components. Our goal is to increase the suitability of the learned features for classification tasks while keeping most of their general representation capability. We analyze the effect of the new methods using visualization on artificial data and discuss the results on two object test sets with regard to the properties of the found feature representation.
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