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Goldsmiths - University of London

A Tactile-based Fabric Learning and Classification Architecture

Khan, A.A.; Khosravi, M.; Denei, S.; Maiolino, P.; Kasprzak, W.; Mastrogiovanni, F. and cannata, G.. 2017. 'A Tactile-based Fabric Learning and Classification Architecture'. In: IEEE ICIAfs 2016. Galle, United Kingdom. [Conference or Workshop Item]

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Abstract or Description

This paper proposes an architecture for tactile-based fabric learning and classification. The architecture is based on a number of SVM-based learning units, which we call fabric classification cores, specifically trained to discriminate between two fabrics. Each core is based on a specific subset of the fully available set of features, on the basis of their discriminative value, determined using the p-value. During fabric recognition, each core casts a vote. The architecture collects votes and provides an overall classification result. We tested seventeen different fabrics, and the result showed that classification errors are negligible.

Item Type: Conference or Workshop Item (Paper)

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
16 December 2016Accepted
2017Published

Event Location:

Galle, United Kingdom

Item ID:

20198

Date Deposited:

11 Apr 2017 14:17

Last Modified:

20 Jun 2017 11:00

URI: http://research.gold.ac.uk/id/eprint/20198

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