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Recognition on Images from Internet Street View Based on Hierarchical Features Learning with CNNs

Recognition on Images from Internet Street View Based on Hierarchical Features Learning with CNNs

Jian-min Liu, Min-hua Yang
Copyright: © 2018 |Volume: 11 |Issue: 3 |Pages: 13
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781522543220|DOI: 10.4018/JITR.2018070105
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MLA

Liu, Jian-min, and Min-hua Yang. "Recognition on Images from Internet Street View Based on Hierarchical Features Learning with CNNs." JITR vol.11, no.3 2018: pp.62-74. http://doi.org/10.4018/JITR.2018070105

APA

Liu, J. & Yang, M. (2018). Recognition on Images from Internet Street View Based on Hierarchical Features Learning with CNNs. Journal of Information Technology Research (JITR), 11(3), 62-74. http://doi.org/10.4018/JITR.2018070105

Chicago

Liu, Jian-min, and Min-hua Yang. "Recognition on Images from Internet Street View Based on Hierarchical Features Learning with CNNs," Journal of Information Technology Research (JITR) 11, no.3: 62-74. http://doi.org/10.4018/JITR.2018070105

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Abstract

This article describes hierarchical features with unsupervised learning on images from internet street view images. This is due to the time spent by trained researchers on feature construction steps with traditional methods. This article focuses on the activation of each layer of with convolutional neural networks (CNNs) on Internet street view images detection and compared similarities and differences among them on each layer. The experiment results achieved error rates of 21% on recognition which work went relatively well than the traditional machine learning techniques, such as Parallel SVM.

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