Learning Robust Embedding Representation With Hybrid Loss for Classification and Verification
This paper presents a method of building an embedding representation via deep metric learning, which works well in both classification and verification problems. The embedding is built via a proposed hybrid loss, which consists of a softmax loss and a Euclidean-metric loss. The hybrid loss explores...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8624290/ |