Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks
IEEE Transactions on Neural Networks and Learning Systems(2021)
摘要
While most deep learning architectures are built on convolution, alternative foundations such as morphology are being explored for purposes such as interpretability and its connection to the analysis and processing of geometric structures. The morphological hit-or-miss operation has the advantage that it considers both foreground information and background information when evaluating the target sh...
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关键词
Transforms,Convolution,Shape,Morphology,Artificial neural networks,Gray-scale,Machine learning
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