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Unsupervised invariance learning of transformation sequences in a model of object recognition yields selectivity for non-accidental properties
Non-accidental properties (NAPs) correspond to image properties that are invariant to changes in viewpoint (e.g., straight vs. curved contours) and are distinguished from metric properties (MPs) that can change continuously with in-depth object rotation (e.g., aspect ratio, degree of curvature, etc....
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Frontiers Media S.A.
2015
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4595784/ https://www.ncbi.nlm.nih.gov/pubmed/26500528 http://dx.doi.org/10.3389/fncom.2015.00115 |