Object classification using basic-level categories
| Autor: | Wojciech Lorkiewicz, Mariusz Mulka, Radosław Katarzyniak |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Computational model
business.industry 020209 energy 05 social sciences Cognitive computing Cue validity 02 engineering and technology Object (computer science) Machine learning computer.software_genre Perceptron Semantics Set (abstract data type) 0202 electrical engineering electronic engineering information engineering Artificial intelligence 0509 other social sciences 050904 information & library sciences Precision and recall business computer |
| Zdroj: | CISP-BMEI |
| Popis: | This paper introduces a computational solution allowing an artificial system to organise large datasets into a set of known basic-level categories. Following cognitive computing paradigm we present an approach towards category-based internal organisation of cognitive agent's semantic memory. In particular, assuming a given set of basic-level categories (predefined or developed) we provide a concise introduction to two perceptron-based computational models allowing an artificial system to classify objects into basic-level categories. Utilising results from other disciplines (psychology, linguistics and cognitive science) we take advantage of the notion of cue validity and incorporate it as underlying weights of input features. Finally, using real bird species dataset we highlight simulation results of classification's precision and recall measures. |
| Databáze: | OpenAIRE |
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