Jennifer R. Kwapisz

Computer Vision and Pattern Recognition · 2010–2011

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 43 researchers here, as inferred from the citation graph.

Subfields

Whom Jennifer R. Kwapisz trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Gary M. Weiss
  2. Jonathan Lester
  3. Tanzeem Choudhury
  4. Davrondzhon Gafurov
  5. Ian H. Witten
  6. Nishkam Ravi
  7. Uwe Maurer
  8. Emmanuel Munguia Tapia
  9. Foster J. Provost
  10. Gaetano Borriello

Who trusts Jennifer R. Kwapisz overall

  1. Gary M. Weiss
  2. Agata Brajdic
  3. Sreenivasan Ramasamy Ramamurthy
  4. Yuqing Chen
  5. Sebastijan Sprager
  6. Timo Sztyler
  7. Ahmet Turan Özdemir
  8. Davide Anguita
  9. Akram Bayat
  10. Jorge Luis Reyes-Ortiz

Papers from Jennifer R. Kwapisz's perspective

Ordered by how strongly the researchers Jennifer R. Kwapisz trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Activity Recognition from User-Annotated Acceleration Data
  2. Activity Recognition from Accelerometer Data (AAAI Conference on Artificial Intelligence)
  3. Activity and Location Recognition Using Wearable Sensors (IEEE pervasive computing)
  4. Identifying users of portable devices from gait pattern with accelerometers (Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.)
  5. Activity recognition and monitoring using multiple sensors on different body positions (International Conference on Wearable and Implantable Body Sensor Networks)
  6. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction (Journal of Artificial Intelligence Research)
  7. Real-Time Recognition of Physical Activities and Their Intensities Using Wireless Accelerometers and a Heart Rate Monitor (International Semantic Web Conference)
  8. Classification of basic daily movements using a triaxial accelerometer (Medical and Biological Engineering and Computing)
  9. The Mobile Sensing Platform: An Embedded Activity Recognition System (IEEE pervasive computing)
  10. Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application (ACM International Conference on Embedded Networked Sensor Systems)

Their papers