Deep learning-based classification with improved time resolution for physical activities of children

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Deep learning-based classification with improved time resolution for physical activities of children

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im Januar 2018 veröffentlichter wissenschaftlicher Artikel

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wetenschappelijk artikel

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наукова стаття, опублікована у 2018

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Deep learning-based classifica ...... hysical activities of children

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Deep learning-based classifica ...... hysical activities of children

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Deep learning-based classifica ...... hysical activities of children

@en

Deep learning-based classifica ...... hysical activities of children

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Deep learning-based classifica ...... hysical activities of children

@en

Deep learning-based classifica ...... hysical activities of children

@nl

P1476

Deep learning-based classifica ...... hysical activities of children

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P2093

Doheon Lee

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Kiseong Kim

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Seunghwan Kim

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Yongwon Jang

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P2860

Long-term activity recognition from wristwatch accelerometer data.

A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data.

Activity classification based on inertial and barometric pressure sensors at different anatomical locations.

Estimation of energy expenditure using prediction equations in overweight and obese adults: a systematic review.

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients.

Artificial neural networks to predict activity type and energy expenditure in youth.

Intensity of bouted and sporadic physical activity and the metabolic syndrome in adults

Comparison between Mother, ActiGraph wGT3X-BT, and a hand tally for measuring steps at various walking speeds under controlled conditions.

Smart approaches for assessing free-living energy expenditure following identification of types of physical activity.

Feature selection and activity recognition system using a single triaxial accelerometer.

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e5764

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scholarly article

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10.7717/PEERJ.5764

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P407

English

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P577

2018-01-01T00:00:00Z

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30364555

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6197045

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