Soichiro Takata

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This paper proposes an anomaly detection method for sound signals observed from motors in operation without using abnormal signals. It is based on feature emphasis and effectively detects anomalies that appear in a small subset of features. To emphasize the features, the method optimally estimates the contribution rates of various features to the(More)
in silico modeling of smiling motions (maximum lip corner retraction) was achieved using the recorded 3-dimensional motion data of 10 anatomical landmarks on a face for 60 women (30 young adults and 30 middle-aged adults). A total of 55 feature variables were extracted from the motion data to generate a feature vector. Sets of the feature vector and the age(More)
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