Toward Flexible and Efficient Home Context Sensing: Capability Evaluation and Verification of Image-Based Cognitive APIs

Sensors
Sinan ChenMasahide Nakamura

Abstract

Cognitive Application Program Interface (API) is an API of emerging artificial intelligence (AI)-based cloud services, which extracts various contextual information from non-numerical multimedia data including image and audio. Our interest is to apply image-based cognitive APIs to implement flexible and efficient context sensing services in a smart home. In the existing approach with machine learning by us, with the complexity of recognition object and the number of the defined contexts increases by users, it still requires directly manually labeling a moderate scale of data for training and continually try to calling multiple cognitive APIs for feature extraction. In this paper, we propose a novel method that uses a small scale of labeled data to evaluate the capability of cognitive APIs in advance, before training features of the APIs with machine learning, for the flexible and efficient home context sensing. In the proposed method, we exploit document similarity measures and the concepts (i.e., internal cohesion and external isolation) integrate into clustering results, to see how the capability of different cognitive APIs for recognizing each context. By selecting the cognitive APIs that relatively adapt to the defined cont...Continue Reading

References

Jan 20, 2006·The Journal of Physical Chemistry. a·D R RoyP K Chattaraj
Dec 13, 2006·Nature Biotechnology·William S Noble
Dec 22, 2009·Molecular BioSystems·Pierre GeurtsLouis Wehenkel
Jul 12, 2018·IEEE Journal of Biomedical and Health Informatics·Munkhjargal GochooShih-Chia Huang
Aug 20, 2019·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Xinhang SongGongwei Chena

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Methods Mentioned

BETA
feature extraction

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Word2Vec
Clarifai API
Imagga REST ( Imagga )
Doc2Vec
Microsoft Azure Machine Learning
Imagga
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ParallelDots
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