Prof Krikor Ozanyan FInstP FIET FHArp SMIEEE

Professor of Photonic Sensors & Systems

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ORCID: 0000-0001-5923-0298
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Publications

1 - 10 out of 235Page size: 10
  1. 2021
  2. Published

    Fusion from Multimodal Gait Spatiotemporal Data for Human Gait Speed Classifications

    Alharthi, A. & Ozanyan, K., 31 Oct 2021, p. 1. 4 p.

    Research output: Contribution to conference › Paper › peer-review

    DOI: 10.1109/SENSORS47087.2021.9639816
  3. Published

    Spatiotemporal Analysis by Deep Learning of Gait Signatures from Floor Sensors

    Alharthi, A., Casson, A. & Ozanyan, K., 7 May 2021, In: IEEE Sensors Journal. 21, 15, p. 16904 - 16914 10 p.

    Research output: Contribution to journal › Article › peer-review

    DOI: 10.1109/JSEN.2021.3078336
  4. Published

    Gait Activity Classification using Multi-Modality Sensor Fusion: A Deep Learning Approach

    YUNAS, S. U. & Ozanyan, K., 5 May 2021, In: IEEE Sensors Journal. 21, 09424038.

    Research output: Contribution to journal › Article › peer-review

    DOI: 10.1109/JSEN.2021.3077698
  5. Published

    Gait Spatiotemporal Signal Analysis for Parkinsons Disease Detection and Severity Rating

    Alharthi, A., Casson, A. & Ozanyan, K., 15 Jan 2021, In: IEEE Sensors Journal. 21, 2, p. 1838 - 1848 11 p., 9171856.

    Research output: Contribution to journal › Article › peer-review

    DOI: 10.1109/JSEN.2020.3018262
  6. 2020
  7. Published

    Gait Activity Classification From Feature-Level Sensor Fusion of Multi-Modality Systems

    YUNAS, S. U. & Ozanyan, K., 5 Oct 2020, In: IEEE Sensors Journal. 21, 4, p. 4801-4810 10 p.

    Research output: Contribution to journal › Article › peer-review

    DOI: 10.1109/JSEN.2020.3028697
  8. Published

    Age-Related Differences in Healthy Adults Walking Patterns Under a Cognitive Task With Deep Neural Networks

    Costilla-Reyes, O., Scully, P., Leroi, I. & Ozanyan, K., 2 Sep 2020, In: IEEE Sensors Journal. 21, 2, p. 2353-2363 11 p.

    Research output: Contribution to journal › Article › peer-review

    DOI: 10.1109/JSEN.2020.3021349
  9. Published

    Multi-modality sensor fusion for gait classification using deep learning

    YUNAS, S. U., Alharthi, A. & Ozanyan, K., 11 Mar 2020, p. 1-6. 6 p.

    Research output: Contribution to conference › Paper › peer-review

    DOI: 10.1109/SAS48726.2020.9220037
  10. Published

    Sensor fusion for analysis of gait under cognitive load: deep learning approach

    Alharthi, A. S., YUNAS, S. U. & Ozanyan, K. B., 11 Mar 2020, p. 1-6. 6 p.

    Research output: Contribution to conference › Paper › peer-review

    DOI: 10.1109/SAS48726.2020.9220046
  11. Published

    Sensors Fusion for Cognitive Load Analysis using Gait Data

    Alharthi, A. & Ozanyan, K., 25 Feb 2020, University of Manchester, Department of Electrical and Electronic Engineering.

    Research output: Other contribution

    DOI: https://doi.org/10.5281/zenodo.6344738
  12. Published

    Design and implementation of a convolutional neural network on an edge computing smartphone for human activity recognition

    Zebin, T., Scully, P. J., Peek, N., Casson, A. & Ozanyan, K., 2020, In: IEEE Access. 7

    Research output: Contribution to journal › Article › peer-review

    DOI: 10.1109/ACCESS.2019.2941836
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Research Explorer downloads

968
Deep Learning for Monitoring of Human Gait: A Review

Research output: Contribution to journal › Article › peer-review

547
Analysis of Spatio-temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks

Research output: Contribution to journal › Article › peer-review

399
Floor Sensors of Animal Weight and Gait for Precision Livestock Farming

Research output: Contribution to conference › Paper › peer-review

337
Implementation of Non-Intrusive Jet Exhaust Species Distribution Measurements Within a Test Facility

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

272
Implementation of a batch normalized deep LSTM recurrent network on a smartphone for human activity recognition

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review