Integrating Multiple Models Using Image-as-Documents Approach for Recognizing Fine-Grained Home Contexts

• Chen, Sinan

• 佐伯, 幸郎

• 中村, 匡秀

抄録

To implement fine-grained context recognition that is accurate and affordable for general households, we present a novel technique that integrates multiple image-based cognitive APIs and light-weight machine learning. Our key idea is to regard every image as a document by exploiting "tags" derived by multiple APIs. The aim of this paper is to compare API-based models' performance and improve the recognition accuracy by preserving the affordability for general households. We present a novel method for further improving the recognition accuracy based on multiple cognitive APIs and four modules, fork integration, majority voting, score voting, and range voting.

収録刊行物

• Sensors

  Sensors 20 (3), 666-666, 2020-02

  MDPI

キーワード

• context recognition
• image
• cognitive APIs
• machine learning
• majority voting
• score voting
• range voting
• smart home

詳細情報

• CRID: 1050856995322852992
• NII論文ID: 120006826796
• DOI: 10.3390/s20030666
• ISSN: 14248220
• HANDLE: 20.500.14094/90007020
• Web Site: https://www.mdpi.com/1424-8220/20/3/666/pdf
• 本文言語コード: en
• 資料種別: journal article
• データソース種別:
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  • Crossref
  • CiNii Articles
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