연구동향 분석

Activity Recognition of Workers and Passengers onboard Ships Using Multimodal Sensors in a Smartphone

Rajeev Kumar Piyare(라지브 쿠마 피야레) Seong Ro Lee(이성로) 2014년

논문상세정보
인용/피인용
' Activity Recognition of Workers and Passengers onboard Ships Using Multimodal Sensors in a Smartphone' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 전기통신
  • activity recognition
  • classificationalgorithms
  • feature extraction
  • sensor fusion
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
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' Activity Recognition of Workers and Passengers onboard Ships Using Multimodal Sensors in a Smartphone' 의 참고문헌

  • Waikato environment for knowledge analysis (WEKA)
  • Using mobile phones for activity recognition in Parkinson’s patients
    M. V. Albert J. Frontiers in neurology 3 [2012]
  • Towards physical activity recognition using smartphone sensors
    M. Shoaib Proc. IEEE 10th Int. Conf. Ubiquitous Intelligence & Computing, Vietri sul Mare, Italy : 80 ~ 87 [2013]
  • The prediction of speed and incline in outdoor running in humans using accelerometry
    R. Herren Medicine and science in sports and exercise 31 : 1053 ~ 1059 [1999]
  • Recognizing group activities using wearable sensors
    D. Gordon Proc. Mobile and Ubiquitous Systems : Computing, Networking, and Services 104 : 350 ~ 361 [2012]
  • Recognizing context for annotating a live life recording
    N. Kern Personal and Ubiquitous Comput 11 : 251 ~ 263 [2007]
  • Optimal placement of accelerometers for the detection of everyday activities
    I. Cleland J. Sensors 13 : 9183 ~ 9200 [2013]
  • Mobile and Ubiquitous Systems:Computing, Networking, and Services : 188 ~ 199
    T. M. Do [2013]
  • Design of a wearable sensing system for human motion monitoring in physical rehabilitation
    L. G. Villanueva J. Sensors 13 (6) : 7735 ~ 7755 [2013]
  • Data Mining:Practical Machine Learning Tools and Techniques: Practical Machine Learning Tools and Techniques
    I. H. Witten Elsevier [2005]
  • Cross-people mobile-phone based activity recognition
    Z. Zhao Proc. 22nd Int. Joint Conf. Artificial Intelligence 3 : 2545 ~ 2550 [2011]
  • Classification accuracies of physical activities using smartphone motion sensors
    W. Wu J. Medical Internet Research 14 [2012]
  • Centinela : A human activity recognition system based on acceleration and vital sign data
    Ó. D. Lara Pervasive and Mobile Computing 8 : 717 ~ 729 [2011]
  • Activity recognition from user-annotated acceleration data
    L. Bao in Proc. Pervasive Computing 3001 : 1 ~ 17 [2004]
  • Activity recognition from accelerometer data
    Dandekar, N. Littman, M. L. Mysore, P. Ravi, N. in AAAI 5 : 1541 ~ 1546 [2005]
  • Activity Recognition using Cell Phone Accelerometers
    J. R. Kwapisz ACM SIGKDD Explorations Newsletter 12 : 74 ~ 82 [2010]
  • A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity
    C. V. Bouten IEEE Trans. Biomedical Eng 44 : 136 ~ 147 [1997]
  • A dynamic approach to recognize activities in WSN
    M. A. Awan Int. J. Distrib. Sensor Netw [2013]
  • A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data
    S. J. Preece IEEE Trans. Biomedical Eng 56 : 871 ~ 879 [2009]