Learning the Hit-or-Miss Transform-Based Morphological Neural Networks
Mathematical morphology is well suited for learning interpretable shapes because of its structure-based operations. In this article, we propose techniques to improve the learning of the hit-or-miss transform, a morphological operation developed to detect object shapes by simultaneously matching the...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10960390/ |
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