%0 Journal Article
%T Fabric Recognition Using Zero-Shot Learning
%A Feng Wang
%A Huaping Liu
%A Fuchun Sun
%A Haihong Pan
%J 清华大学学报自然科学版（英文版）
%@ 1878-7606
%D 2019
%R 10.26599/TST.2018.9010095
%X In this work, we use a deep learning method to tackle the Zero-Shot Learning (ZSL) problem in tactile material recognition by incorporating the advanced semantic information into a training model. Our main technical contribution is our proposal of an end-to-end deep learning framework for solving the tactile ZSL problem. In this framework, we use a Convolutional Neural Network (CNN) to extract the spatial features and Long Short-Term Memory (LSTM) to extract the temporal features in dynamic tactile sequences, and develop a loss function suitable for the ZSL setting. We present the results of experimental evaluations on publicly available datasets, which show the effectiveness of the proposed method
%K Zero-Shot-Learning (ZSL)
%K fabric recognition
%K tactile recognition
%K deep learning
%U http://tst.tsinghuajournals.com/EN/10.26599/TST.2018.9010095