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| 1 | Automatic rec- ognition of woven fabric pattern baaed on image processing and BP neural network 显示文摘 | Ruru Pan Weidong Gao Jihong Liu Hongbo Wang | 2011 | Journal of the Textile Institute2011，102，1： | 1 |
| 2 | Automatic recognition of woven fabric based on pattern database 显示文摘 | PAN Ruru GAO Weidong LIU Jihong | 2010 | Fibers and Polymers2010，11，2： | 1 |
| 3 | Deep Neural Network with Strip Pooling for Image Classification of Yarn-Dyed Plaid Fabrics显示文摘Historically,yarn-dyed plaid fabrics(YDPFs)have enjoyed enduring popularity with many rich plaid patterns,but production data are still classified and searched only according to production parameters.The process does not satisfy the visual needs of sample order production,fabric design,and stock management.This study produced an image dataset for YDPFs,collected from 10,661 fabric samples.The authors believe that the dataset will have significant utility in further research into YDPFs.Convolutional neural networks,such as VGG,ResNet,and DenseNet,with different hyperparameter groups,seemed themost promising tools for the study.This paper reports on the authors’exhaustive evaluation of the YDPF dataset.With an overall accuracy of 88.78%,CNNs proved to be effective in YDPF image classification.This was true even for the low accuracy of Windowpane fabrics,which often mistakenly includes the Prince ofWales pattern.Image classification of traditional patterns is also improved by utilizing the strip pooling model to extract local detail features and horizontal and vertical directions.The strip pooling model characterizes the horizontal and vertical crisscross patterns of YDPFs with considerable success.The proposed method using the strip pooling model(SPM)improves the classification performance on the YDPF dataset by 2.64%for ResNet18,by 3.66%for VGG16,and by 3.54%for DenseNet121.The results reveal that the SPM significantly improves YDPF classification accuracy and reduces the error rate of Windowpane patterns as well. | Xiaoting Zhang Weidong Gao Ruru Pan | 2022 | Computer Modeling in Engineering & Sciences2022，，3： | 1 |
| 4 | Automatic recognition of woven fabric patterns based on pattern database显示文摘 | Ruru Pan Weidong Gao Jihong Liu Hongbo Wang | 2010 | Fibers and Polymers2010，，2： | 1 |
| 5 | Dynamic measurement of fabric wrinkle recovery angle by video sequence pro- cessing显示文摘 | Lei Wang Jianli Liu Ruru Pan | 2014 | Textile Research Journal2014，84，7： | 1 |
| 6 | Automatic recognition of woven fabric pattern based on image processing and BP neural network 显示文摘 | PAN Ruru GAO Weidong LIU Jihong | 2011 | The Journal of the Textile Institute2011，102，1： | 1 |
| 7 | Automatic recognition of the color effect of yarn-dyed fabric by the smallest repeat unit recognition algori- thm显示文摘 | ZHANG Jie PAN Ruru GAO Weidong | 2015 | Textile Research Journal2015，85，： | 1 |
| 8 | Automatic recogni- tion of woven fabric pattern based on image processing and BP neural network显示文摘 | Pan Ruru Gao Weidong Liu Jibong | 2011 | Joumal of the Textile Institute2011，102，： | 1 |
| 9 | Automatic recognition of woven fabric pattern based on pattern database显示文摘 | PAN Ruru GAO Weidong LIU Jihong | 2010 | Fibers and Polymers2010，11，2： | 1 |
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