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This paper presents a method for recognition of Activities of Daily Living (ADL) in smart homes.
Based on this fluorescence switch characteristics of PMTH, a new method for recognition and determination of SAM was established.
In this paper, we propose a method for recognition of human actions by analysis of skeleton poses.
This approach, called adaptive Bayesian inference system (BasIS), uses a probabilistic formulation with a sequential analysis method, for recognition of walking activities performed by participants.
Results indicate that our method for recognition of key regions is effective and practical and its application to the HRB identified the Northern Plain area as the key region for restoration.
This section explains the proposed method for recognition.
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Principal Component Analysis (PCA) and Modular PCA (MPCA) are well known statistical methods for recognition of facial images.
Extensive experimental results illustrate that the proposed deep learning approach outperforms state-of-the-art methods for recognition of cattle on muzzle point image database.
These results are contrasted with benchmark methods for recognition in a systematic validation revealing, in particular, an improved performance for mixture model prediction utilizing segments.
Current methods for recognition and interpretation of architectural drawings are limited to either low-level analysis of paper drawings or interpretation of electronic drawings that depicts only high-level design entities.
This special issue presents two novel methods for recognition of individuals based on sample signatures.
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