Fabric Recognition Using Zero-Shot Learning  

作　　者：Feng Wang Huaping Liu Fuchun Sun Haihong Pan 

机构地区：[1]Department of Computer Science and Technology,Tsinghua University,Beijing 100084,China [2]College of Mechanical Engineering,Guangxi University,Nanning 530003,China

出　　处：《Tsinghua Science and Technology》2019年第6期645-653,共9页清华大学学报（自然科学版（英文版）

基　　金：supported in part by the National Natural Science Foundation of China (Nos. 61673238, 61703284, and 61327809);the Beijing Municipal Science and Technology Commission (No. D171100005017002)

摘　　要：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.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.

关 键 词：Zero-Shot-Learning (ZSL) FABRIC recog nition TACTILE recog nition DEEP lear ning 

分 类 号：N[自然科学总论]