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在“Elsevier电子期刊”中，命中：5条，耗时：0.0529424 秒

在所有数据库中总计命中：665条

1.Improving handwritten Chinese text recognition using neural network language models and convolutional neural network shape models

作者：Yi-Chao Wu^a ; ^{yichao.wu@nlpr.ia.ac.cn}Author Vitae ; Fei Yin^a ; ^{fyin@nlpr.ia.ac.cn}Author Vitae ; Cheng-Lin Liu^a ; ^b ; ^c ; ^{liucl@nlpr.ia.ac.cn}Author Vitae

关键词：Handwritten Chinese text recognition ; Feedforward neural network language model ; Recurrent neural network language model ; Hybrid language model ; Convolutional neural network shape models

刊名：Pattern Recognition

出版年：2017

2.Using filter banks in Convolutional Neural Networks for texture classification

作者：Vincent Andrearczyk ; ^{vincent.andrearczyk3@mail.dcu.ie} ; Paul F. Whelan

关键词：Texture classification ; Convolutional Neural Network ; Dense orderless pooling ; Filter banks ; Energy layer

刊名：Pattern Recognition Letters

出版年：2016

3.Image driven machine learning methods for microstructure recognition

作者：Aritra Chowdhury^a ; ^{achowd@rpi.edu" class="auth_mail" title="E-mail the corresponding author} ; Elizabeth Kautz^b ; ^{kautze@rpi.edu" class="auth_mail" title="E-mail the corresponding author} ; Bü ; lent Yener^a ; ^{yener@cs.rpi.edu" class="auth_mail" title="E-mail the corresponding author} ; Daniel Lewis^b ; ^{lewisd2@rpi.edu" class="auth_mail" title="E-mail the corresponding author}

关键词：Microstructure ; Computer vision ; Machine learning ; Classification ; Convolutional neural networks ; Micrograph

刊名：Computational Materials Science

出版年：2016

4.Deep sketch feature for cross-domain image retrieval

作者：Xinggang WangAuthor Vitae ; Xiong DuanAuthor Vitae ; Xiang Bai ; ^{xbai@hust.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae

关键词：Sketch recognition ; Image retrieval ; Deep learning

刊名：Neurocomputing

出版年：2016

5.Can Deep Neural Networks Discover Meaningful Pattern Features?

作者：Iveta Mrazova ; ^{iveta.mrazova@mff.cuni.cz} ; Marek Kukacka ^{mkukacka@gmail.com}

关键词：convolutional neural networks ; image classification ; self-organization ; feature extraction ; pruning ; generalization

刊名：Procedia Computer Science

出版年：2012

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