面向经济实用的家庭环境识别——基于图像认知API的框架与实现

Sinan Chen, S. Saiki, Masahide Nakamura
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引用次数: 6

摘要

为了为普通家庭提供负担得起的上下文识别,本文提出了一种集成基于图像的认知应用程序接口(API)和轻量级机器学习的新技术。我们的关键思想是通过利用API派生的“标签”,将每个图像视为文档。我们首先提出了一个框架,该框架指定了基于机器学习的家庭环境识别的通用工作流程。然后,我们提出了一种实用的方法,该方法使用“图像即文档”方法实现该框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward Affordable and Practical Home Context Recognition: -Framework and Implementation with Image-based Cognitive API-
To provide affordable context recognition for general households, this paper presents a novel technique that integrate image-based cognitive Application Program Interface (API) and light-weight machine learning. Our key idea is to regard every image as a document by exploiting “tags” derived by the API. We first present a framework that specifies a common workflow of the machine-learning-based home context recognition. We then propose a pragmatic method that implements the framework using the “image-as-a-document” approach.
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