Integrating Multiple Models Using Image-as-Documents Approach for Recognizing Fine-Grained Home Contexts
Keyword(s):
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.
2010 ◽
Vol 132
(5)
◽
Keyword(s):
2019 ◽
Vol 12
(1)
◽
pp. 72-74
2020 ◽
Vol 40
(7)
◽
pp. 2542-2547
◽
2015 ◽
Vol 129
(10)
◽
pp. 1025-1027
◽
Keyword(s):