A Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds
- Submitting institution
-
University of Lincoln
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 33420
- Type
- D - Journal article
- DOI
-
10.1109/TCYB.2018.2869384
- Title of journal
- IEEE Transactions on Cybernetics
- Article number
- -
- First page
- 1541
- Volume
- 50
- Issue
- 4
- ISSN
- 2168-2267
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2018
- URL
-
http://doi.org/10.1109/TCYB.2018.2869384
- 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
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Recognizing a small moving target only a few pixles in size with limited computation power and time constrains is challenging - insects are doing this seems effortless. In this paper, a small moving target detector is proposed with mechanisms inspiration from flying insects. It not only detects the location of the small moving targets against complex background, but it is also able to predict the moving direction to track these small moving targets. The method could be used in robots or vehicles for early preparation for action in real-time.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
