Quad-Channel Contrastive Prototype Networks for Open-Set Recognition in Domain-Specific Tasks
A traditional deep neural network-based classifier assumes that only training classes appear during testing in closed-world settings. In most real-world applications, an open-set environment is more realistic than a conventional approach where unseen classes are potentially present during the model&...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10123937/ |