LSI: Latent semantic inference for natural image segmentation
- Submitting institution
-
Queen Mary University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 520
- Type
- D - Journal article
- DOI
-
10.1016/j.patcog.2016.03.005
- Title of journal
- Pattern Recognition
- Article number
- -
- First page
- 282
- Volume
- 59
- Issue
- -
- ISSN
- 0031-3203
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- 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
- No
- Number of additional authors
-
0
- Research group(s)
-
-
- Citation count
- 13
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper is an output of the collaborative PhD supervision of Mr Ning Feng of UESTC (contact: Prof. Le Dong ledong@uestc.edu.cn). This work led to a CSC scholarship for Ning to visit QMUL for one year and finished the last stage of his PhD under my supervision, applying the described techniques in biomedical domain. This research inspired several further joint publications:- Tissue Region Growing for Histopathology Image Segmentation. ICBISP?18; Detection of Breast Tumour Tissue Regions in Histopathological Images using Convolutional Neural Networks, IPAS?18; DNS: A multi-scale deconvolution semantic segmentation network for joint detection and segmentation, MATEC?19.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
