Feature extraction of video using artificial neural network

Yoshihiro Hayakawa, Takanori Oonuma, Hideyuki Kobayashi, Akiko Takahashi, Shinji Chiba, Nahomi M. Fujiki

研究成果: Article査読

抄録

In deep neural networks, which have been gaining attention in recent years, the features of input images are expressed in a middle layer. Using the information on this feature layer, high performance can be demonstrated in the image recognition field. In the present study, we achieve image recognition, without using convolutional neural networks or sparse coding, through an image feature extraction function obtained when identity mapping learning is applied to sandglass-style feed-forward neural networks. In sports form analysis, for example, a state trajectory is mapped in a low-dimensional feature space based on a consecutive series of actions. Here, we discuss ideas related to image analysis by applying the above method.

本文言語English
ページ(範囲)25-40
ページ数16
ジャーナルInternational Journal of Cognitive Informatics and Natural Intelligence
11
2
DOI
出版ステータスPublished - 2017 4 1
外部発表はい

ASJC Scopus subject areas

  • ソフトウェア
  • 人間とコンピュータの相互作用
  • 人工知能

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