Integrating Computational and Neural Findings in Visual Object Perception

• Autore: Hans P. Op de Beeck
• Pubblicazione: Frontiers Media SA, 2016
• Descrizione fisica: 1 electronic resource (137 p.)
• Soggetto non controllato: object recognition; fMRI; multimodal data integration; neural networks; invariance; computational neuroscience; Computer Vision; Feature representation; Neurophysiology; ventral visual pathway
• Persona (resp. second.): Judith C. Peters; Rainer Goebel
• Sommario/riassunto: The articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.
• Titolo autorizzato: Integrating Computational and Neural Findings in Visual Object Perception
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910166647303321
• Lo trovi qui: Univ. Federico II