Paul J. M. Havinga

Computer Vision and Pattern Recognition · 2004–2016

A researcher in the Science corpus: 6 papers; trusts 11 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Paul J. M. Havinga trusts overall

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

  1. Bernt Schiele
  2. D. Segal
  3. Vipin Kumar
  4. Stephen S. Intille
  5. Ling Bao
  6. Tâm Huynh
  7. Hong Lu
  8. Andrew T. Campbell
  9. Nicholas Donald Lane
  10. Varun Chandola

Who trusts Paul J. M. Havinga overall

  1. Hyojeong Shin
  2. Wei Ye
  3. Abdelmalik Bachir
  4. Aristides Mpitziopoulos
  5. Hojung Cha

Papers from Paul J. M. Havinga's perspective

Ordered by how strongly the researchers Paul J. M. Havinga 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. Analyzing features for activity recognition (sOc-EUSAI '05)
  4. Efficient algorithms for mining outliers from large data sets (ACM SIGMOD Conference)
  5. Activity sensing in the wild: a field trial of ubifit garden (International Conference on Human Factors in Computing Systems)
  6. The WEKA data mining software: an update
  7. Recognizing human motion with multiple acceleration sensors (2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236))
  8. Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring (IEEE Transactions on Information Technology in Biomedicine)
  9. Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly (IEEE Transactions on Biomedical Engineering)
  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