Brain-Computer Interfaces for Detection and Localization of Targets in Aerial Images
- Submitting institution
-
The University of Essex
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1089
- Type
- D - Journal article
- DOI
-
10.1109/TBME.2016.2583200
- Title of journal
- IEEE Transactions on Biomedical Engineering
- Article number
- 4
- First page
- 959
- Volume
- 64
- Issue
- 4
- ISSN
- 0018-9294
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2016
- 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
-
1
- Research group(s)
-
B - Brain Computer Interfaces and Neural Engineering (BCI-NE)
- Citation count
- 11
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This is the first brain-computer interface (BCI) capable of detecting AND spatially locating targets in real-world images presented at high framerate, applicable to high-speed aerial/satellite-image sifting by intelligence agencies. Our BCI is a major-step towards increasing throughput of such processes and initiated informal industrial discussions about use outside of intelligence e.g., removing police-officers from assessments of harrowing images. The paper also demonstrated accurate inference of user handedness from brain-signals. The underpinning brain-signals dataset has been used by others to explore transfer learning, a very hot-topic in BCIs, in addition to benchmarking algorithms to detect targets in images from brain-signals.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -