Incrementally Learning Objects by Touch: Online Discriminative and Generative Models for Tactile-Based Recognition

Human beings not only possess the remarkable ability to distinguish objects through tactile feedback but are further able to improve upon recognition competence through experience. In this work, we explore tactile-based object recognition with learners capable of incremental learning. Using the spar...

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Bibliographic Details
Published in:	IEEE transactions on haptics Vol. 7; no. 4; pp. 512 - 525
Main Authors:	Soh, Harold, Demiris, Yiannis
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.10.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Adult Algorithms Artificial Intelligence Classifications Classifiers Cluster Analysis Discriminant Analysis Female Grasping Hand Strength Humans Learning Learning systems Male Models, Theoretical Object recognition Online Online Systems Palpation Pattern Recognition, Automated - methods Robotics - methods Support vector machines Tactile Tactile sensors Teachers Touch Training Unsupervised learning Young Adult supervised classification incremental learning Tactile object recognition unsupervised learning
ISSN:	1939-1412, 2329-4051, 2329-4051
Online Access:	Get full text
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