A novel approach to reconstruction based saliency detection via convolutional neural network stacked with auto-encoder
- Submitting institution
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Glasgow Caledonian University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 33289762
- Type
- D - Journal article
- DOI
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10.1016/j.neucom.2019.01.041
- Title of journal
- Neurocomputing
- Article number
- -
- First page
- 145
- Volume
- 349
- Issue
- -
- ISSN
- 0925-2312
- Open access status
- Compliant
- Month of publication
- January
- Year of publication
- 2019
- URL
-
-
- Supplementary information
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-
- 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
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4
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper is one of many positive outcomes of the long-term collaboration with East China University of Science and Technology, Shanghai, China, (through the Collaborative Research Group of Artificial Intelligence, which is a group in the Ministry of Education Key Laboratory of Advanced Control and Optimization for Chemical Processes at East China University of Science and Technology). The work was funded by the Chinese government, through the National Key R&D Programme of China, the National Natural Science Foundation of China and the International Cooperation and Exchange Programme.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -