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Shearlets as Feature Extractor for Semantic Edge Detection: The Model-Based and Data-Driven Realm
[article]
2019
arXiv
pre-print
Semantic edge detection has recently gained a lot of attention as an image processing task, mainly due to its wide range of real-world applications. This is based on the fact that edges in images contain most of the semantic information. Semantic edge detection involves two tasks, namely pure edge detecion and edge classification. Those are in fact fundamentally distinct in terms of the level of abstraction that each task requires, which is known as the distracted supervision paradox that
arXiv:1911.12159v1
fatcat:hebhvk7sgjc6toglbbk2syjto4