Nicholas Luke Seed

Computer Vision and Pattern Recognition · 2013

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Nicholas Luke Seed trusts overall

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

  1. Caroline Rougier

Who trusts Nicholas Luke Seed overall

  1. Michal Kepski

Papers from Nicholas Luke Seed's perspective

Ordered by how strongly the researchers Nicholas Luke Seed trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Fall detection - Principles and Methods (Annual International Conference of the IEEE Engineering in Medicine and Biology Society)
  2. A Smart and Passive Floor-Vibration Based Fall Detector for Elderly (2006 2nd International Conference on Information & Communication Technologies)
  3. A smart sensor to detect the falls of the elderly (IEEE pervasive computing)
  4. Fall Detection from Human Shape and Motion History Using Video Surveillance (21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07))
  5. Monitoring behavior in home using a smart fall sensor and position sensors (1st Annual International IEEE-EMBS Special Topic Conference on Microtechnologies in Medicine and Biology. Proceedings (Cat. No.00EX451))
  6. A Method for Automatic Fall Detection of Elderly People Using Floor Vibrations and Sound—Proof of Concept on Human Mimicking Doll Falls (IEEE Transactions on Biomedical Engineering)
  7. Entorhinal/dentate excitation of CA3: A critical variable in hippocampal models (Neurocomputing)
  8. Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring (IEEE Transactions on Information Technology in Biomedicine)
  9. Robust Video Surveillance for Fall Detection Based on Human Shape Deformation (IEEE transactions on circuits and systems for video technology (Print))
  10. Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement (Physiological Measurement)

Their papers