A Tactile-based Fabric Learning and Classification Architecture
A. Khan , P. Maiolino , M. Khosravi , Włodzimierz Kasprzak
AbstractThis 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.
|Publication size in sheets||0.5|
|Book||2016 IEEE International Conference on Information and Automation for Sustainability, 2016, IEEE|
|Score|| = 15.0, 03-06-2020, BookChapterMatConfByConferenceseries|
= 15.0, 03-06-2020, BookChapterMatConfByConferenceseries
|Publication indicators||= 0; = 1|
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