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Distress Image Retrieval for Infrastructure Maintenance via Self-Trained Deep Metric Learning Using Experts' Knowledge
- Source :
- IEEE Access. 9:65234-65245
- Publication Year :
- 2021
- Publisher :
- IEEE (Institute of Electrical and Electronics Engineers), 2021.
-
Abstract
- Distress image retrieval for infrastructure maintenance via self-trained deep metric learning using experts’ knowledge is proposed in this paper. Since engineers take multiple images of a single distress part for inspection of road structures, it is necessary to construct a similar distress image retrieval method considering the input of multiple images to support determination of the level of deterioration. Thus, the construction of an image retrieval method while selecting an effective input from multiple images is described in this paper. The proposed method performs deep metric learning by using a small number of effective images labeled by experts’ knowledge with information about their effectiveness and a large number of unlabeled images via a self-training approach. Specifically, an end-to-end learning approach that performs retraining of the model by assigning pseudo-labels to these unlabeled images according to the output confidence of the model is achieved. Thus, the proposed method can select an effective image from multiple images that are input at the retrieval as a query image. This is the main contribution of this paper. As a result, the proposed method realizes highly accurate retrieval of similar distress images considering the actual situation of inspection in which multiple images of a distress part are input.
- Subjects :
- General Computer Science
Computer science
deep metric learning
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
0211 other engineering and technologies
02 engineering and technology
Machine learning
computer.software_genre
Maintenance engineering
Image (mathematics)
pseudo-label
021105 building & construction
0202 electrical engineering, electronic engineering, information engineering
Training
General Materials Science
Image retrieval
Measurement
Training data
self-trained approach
business.industry
Inspection
General Engineering
Retraining
Construct (python library)
Distress image retrieval
Distress
Metric (mathematics)
Task analysis
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....b455959e46273ef36615f61401aee7e8