Works (4)

Updated: July 5th, 2023 15:41

2017 conference paper

Energy-efficient activity recognition via multiple time-scale analysis

2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1466–1472.

By: N. Lokare n, S. Samadi n, B. Zhong n, L. Gonzalez n, F. Mohammadzadeh n & E. Lobaton n

TL;DR: This work proposes a novel power-efficient strategy for supervised human activity recognition using a multiple time-scale approach, which takes into account various window sizes, and shows that the proposed approach Sequential Maximum-Likelihood achieves high F1 score across all activities while providing lower power consumption than the standard Maximum- likelihood approach. (via Semantic Scholar)
UN Sustainable Development Goal Categories
7. Affordable and Clean Energy (OpenAlex)
Sources: NC State University Libraries, NC State University Libraries, ORCID
Added: August 6, 2018

2017 conference paper

Robust trajectory-based density estimation for geometric structure recovery

2017 25th European Signal Processing Conference (EUSIPCO), 1210–1214.

By: T. Richmond n, N. Lokare n & E. Lobaton n

TL;DR: This work proposes a method to both quickly and robustly extract geometric information from trajectory data and finds an improvement in performance over the current practice in that the method is able to extract only the salient data and ignore trajectory outliers. (via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities (OpenAlex)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018

2016 conference paper

Comparing wearable devices with wet and textile electrodes for activity recognition

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 3539–3542.

By: N. Lokare n, L. Gonzalez n & E. Lobaton n

MeSH headings : Artifacts; Electrocardiography / instrumentation; Electrocardiography / methods; Electrodes; Equipment Design; Humans; Muscle, Skeletal / physiology; Principal Component Analysis; Signal Processing, Computer-Assisted; Textiles
TL;DR: It is observed that signals from the dry textile electrodes introduce less artifacts associated with muscle activation, so it is possible to obtain good performance for both the wet and dry electrodes. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID, NC State University Libraries
Added: August 6, 2018

2015 article

Non-Rigid Image Registration under Non-Deterministic Deformation Bounds

(E. Romero & N. Lepore, Eds.). 10TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS, Vol. 9287.

By: Q. Ge n, N. Lokare n & E. Lobaton n

Ed(s): E. Romero & N. Lepore

author keywords: Non-rigid image registration; Lipschitz deformation; Uncertainty quantification
TL;DR: An approach for identifying point correspondences with zero false-negative rate and high precision is introduced under the assumption that two images of the same anatomic structure are related via a Lipschitz non-rigid deformation (the registration map). (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018

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