A Weakly-Supervised Semantic Segmentation Approach Based on the Centroid Loss: Application to Quality Control and Inspection
It is generally accepted that one of the critical parts of current vision algorithms based on deep learning and convolutional neural networks is the annotation of a sufficient number of images to achieve competitive performance. This is particularly difficult for semantic segmentation tasks since th...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9424002/ |