Update search
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
Filter
- All
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- EISBN
- ISSN
- EISSN
- Issue
- Volume
- References
NARROW
Format
Journal
Type
Date
Availability
1-2 of 2
Keywords: Semantic segmentation
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Journal Articles
Journal:
Industrial Lubrication and Tribology
Industrial Lubrication and Tribology (2025) 77 (2): 211–218.
Published: 18 December 2024
...-0182/ Jingming Li can be contacted at: jmli@shmtu.edu.cn 01 06 2024 22 09 2024 01 11 2024 © Emerald Publishing Limited 2024 Emerald Publishing Limited Licensed re-use rights only Ferrographic image Mask R-CNN Transfer learning Semantic segmentation Wear debris...
Journal Articles
Journal:
Industrial Lubrication and Tribology
Industrial Lubrication and Tribology (2022) 74 (7): 884–891.
Published: 27 July 2022
... sliding wear particles, which are similar in morphology while different in wear mechanism. Design/methodology/approach A CNN model named DWear is proposed to semantically segment fatigue, severe sliding particles and four other types of particles, that is, chain, spherical, cutting and oxide particles...
