Natural categorization through multiple feature learning in pigeons.

作者: Ludwig Huber , Nikolaus F.T roje , Michaela Loidolt , Ulrike Aust , Dieter Grass

DOI: 10.1080/713932733

关键词: Feature (computer vision)PsychologyNatural (music)Discriminant function analysisPrincipal component analysisCategorizationFlexibility (personality)CommunicationVisual texturePattern recognitionArtificial intelligenceFeature learning

摘要: Recently (Troje, Huber, Loidolt, Aust, & Fieder 1999), we found that pigeons discriminated between large sets of photorealistic frontal images human faces on the basis sex. This ability was predominantly based information contained in visual texture those rather than their configural properties. The could learn distinction even when differences shape and average intensity were completely removed. Here, proved more specifically pigeons' flexibility efficiency to utilize class-distinguishing complex natural classes. First, used principal component as well discriminant function analysis order determine which aspects male female support successful categorization. We then conducted various tests involving systematic transformations reduction feature content examine whether or not categorization behaviour comes under control categorylevel dimensions—that ...

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