Joshua Ellul

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 18 citations into it
• Biomedical Engineering — 16 citations into it
• Electrical and Electronic Engineering — 5 citations into it

Whom Joshua Ellul trusts overall

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

1. Bogdan Kwolek
2. Michal Kepski
3. W. Deng
4. Caroline Rougier
5. Mingmin Zhao

Papers from Joshua Ellul's perspective

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

1. Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm.
2. Fall detection system using Kinect’s infrared sensor (Journal of Real-Time Image Processing)
3. Comparison of low-complexity fall detection algorithms for body attached accelerometers. (Gait & Posture)
4. Challenges, issues and trends in fall detection systems (BioMedical Engineering OnLine)
5. Deep Learning
6. UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
7. Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information (2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks)
8. A survey of depth and inertial sensor fusion for human action recognition
9. Fall detection using ceiling-mounted 3D depth camera
10. A wearable health care system based on knitted integrated sensors (IEEE Transactions on Information Technology in Biomedicine)

Their papers

• Elderly Fall Detection Systems: A Literature Survey (2020) — 314 citations