Cargando…
Object Learning Improves Feature Extraction but Does Not Improve Feature Selection
A single glance at your crowded desk is enough to locate your favorite cup. But finding an unfamiliar object requires more effort. This superiority in recognition performance for learned objects has at least two possible sources. For familiar objects observers might: 1) select more informative image...
Autores principales: | Holm, Linus, Engel, Stephen, Schrater, Paul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3520912/ https://www.ncbi.nlm.nih.gov/pubmed/23251499 http://dx.doi.org/10.1371/journal.pone.0051325 |
Ejemplares similares
-
Episodic curiosity for avoiding asteroids: Per-trial information gain for choice outcomes drive information seeking
por: Holm, Linus, et al.
Publicado: (2019) -
Feature extraction and selection for objective gait analysis and fall risk assessment by accelerometry
por: Caby, Benoit, et al.
Publicado: (2011) -
How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?
por: Ghodrati, Masoud, et al.
Publicado: (2012) -
Grasping Objects with Environmentally Induced Position Uncertainty
por: Christopoulos, Vassilios N., et al.
Publicado: (2009) -
Improved WOA and its application in feature selection
por: Liu, Wei, et al.
Publicado: (2022)