This paper addresses the problem of learning and efficiently representing discriminative probabilistic models of object-specific grasp affordances ...
Abstract—This paper addresses the problem of learning and efficiently representing discriminative probabilistic models of object-specific grasp affordances ...
This paper addresses the problem of learning and efficiently representing discriminative probabilistic models of object-specific grasp affordances particularly ...
PDF | This paper addresses the problem of learning and efficiently representing discriminative probabilistic models of object-specific grasp affordances.
This paper addresses the problem of learning and efficiently representing discriminative probabilistic models of object-specific grasp affordances ...
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Learning probabilistic discriminative models of grasp affordances under limited supervision. In 2010 IEEE/RSJ International Conference on Intelligent Robots ...
Learning probabilistic discriminative models of grasp affordances ...
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In this paper, we propose a novel hybrid discriminative learning approach based on shifted-scaled Dirichlet mixture model (SSDMM) and Support Vector Machines ( ...
Robot Learning Lecture · Robot Learning ... ", year = "2010", title = "Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision ...
Erkan, O. ; Detry, R. ; Altun, Y. ; Piater, J. ; Peters, J. (2010) Learning Probabilistic Discriminative Models of Grasp Affordances under Limited Supervision.
Apr 25, 2024 · Learning probabilistic discriminative models of grasp affordances under limited supervision. ... Deep belief net learning in a long-range ...