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Automatic Tagging for Social Images using Convolution Neural Networks
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  • Journal title : Journal of KIISE
  • Volume 43, Issue 1,  2016, pp.47-53
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2016.43.1.47
 Title & Authors
Automatic Tagging for Social Images using Convolution Neural Networks
Jang, Hyunwoong; Cho, Soosun;
 
 Abstract
While the Internet develops rapidly, a huge amount of image data collected from smart phones, digital cameras and black boxes are being shared through social media sites. Generally, social images are handled by tagging them with information. Due to the ease of sharing multimedia and the explosive increase in the amount of tag information, it may be considered too much hassle by some users to put the tags on images. Image retrieval is likely to be less accurate when tags are absent or mislabeled. In this paper, we suggest a method of extracting tags from social images by using image content. In this method, CNN(Convolutional Neural Network) is trained using ImageNet images with labels in the training set, and it extracts labels from instagram images. We use the extracted labels for automatic image tagging. The experimental results show that the accuracy is higher than that of instagram retrievals.
 Keywords
automatic image tagging;convolutional neural network;image content;instagram;
 Language
Korean
 Cited by
1.
이미지와 텍스트 정보의 카테고리 분류에 의한 SNS 팔로잉 추천 방법,홍택은;신주현;

스마트미디어저널, 2016. vol.5. 3, pp.54-61
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