Analysis of Spatio-temporal Representations for Robust Footstep Recognition with Deep Residual Neural Networks
- Submitting institution
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The University of Manchester
- Unit of assessment
- 12 - Engineering
- Output identifier
- 64803537
- Type
- D - Journal article
- DOI
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10.1109/TPAMI.2018.2799847
- Title of journal
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Article number
- 8275035
- First page
- 285
- Volume
- 41
- Issue
- 2
- ISSN
- 0162-8828
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
2
- Research group(s)
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F - EEE
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Research pioneered in this work was taken further to win awards in 2019 and 2020 for linking ANN classifications to clinical practice observables (Best Technical Paper award - IDEAL, 2019) and multimodality sensor fusion with floor sensors (Best Paper award - IEEE SAS, 2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
