Towards a theoretical framework for learning multi-modal patterns for embodied agents
Noceti N, Caputo B, Baldassarre L, Barla A, Rosasco L, Odone F, Sandini G, Castellini C (2009)
Publication Type: Conference contribution
Publication year: 2009
Journal
Book Volume: 5716 LNCS
Pages Range: 239-248
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: ITA
ISBN: 3642041450
DOI: 10.1007/978-3-642-04146-4_27
Abstract
Multi-modality is a fundamental feature that characterizes biological systems and lets them achieve high robustness in understanding skills while coping with uncertainty. Relatively recent studies showed that multi-modal learning is a potentially effective add-on to artificial systems, allowing the transfer of information from one modality to another. In this paper we propose a general architecture for jointly learning visual and motion patterns: by means of regression theory we model a mapping between the two sensorial modalities improving the performance of artificial perceptive systems. We present promising results on a case study of grasp classification in a controlled setting and discuss future developments. © 2009 Springer Berlin Heidelberg.
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Italy (IT)How to cite
APA:
Noceti, N., Caputo, B., Baldassarre, L., Barla, A., Rosasco, L., Odone, F.,... Castellini, C. (2009). Towards a theoretical framework for learning multi-modal patterns for embodied agents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 239-248). ITA.
MLA:
Noceti, Nicoletta, et al. "Towards a theoretical framework for learning multi-modal patterns for embodied agents." Proceedings of the 15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings, ITA 2009. 239-248.
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