ILSVRC on a Smartphone
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- Kawano Yoshiyuki
- Department of Informatics, The University of Electro-Communications
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- Yanai Keiji
- Department of Informatics, The University of Electro-Communications
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説明
In this work, to the best of our knowledge, we propose a stand-alone large-scale image classification system running on an Android smartphone. The objective of this work is to prove that mobile large-scale image classification requires no communication to external servers. To do that, we propose a scalar-based compression method for weight vectors of linear classifiers. As an additional characteristic, the proposed method does not need to uncompress the compressed vectors for evaluation of the classifiers, which brings the saving of recognition time. We have implemented a large-scale image classification system on an Android smartphone, which can perform 1000-class classification for a given image in 0.270 seconds. In the experiment, we show that compressing the weights to 1/8 leaded to only 0.80% performance loss for 1000-class classification with the ILSVRC2012 dataset. In addition, the experimental results indicate that weight vectors compressed in low bits, even in the binarized case (bit =1), are still valid for classification of high dimensional vectors.
収録刊行物
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- Information and Media Technologies
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Information and Media Technologies 9 (3), 371-375, 2014
Information and Media Technologies 編集運営会議
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詳細情報 詳細情報について
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- CRID
- 1390282680242570368
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- NII論文ID
- 130004687732
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- ISSN
- 18810896
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可
