Morphological Processing
The recent impressive results of deep learning-based methods on computer vision applications brought fresh air to the research and industrial community. This success is mainly due to the process that allows those methods to learn data-driven features, generally based upon linear operations. However, in some scenarios, such operations do not have a good performance because of their inherited process that blurs edges, losing notions of corners, borders, and geometry of objects. Overcoming this, non-linear operations, such as morphological ones, may preserve such properties of the objects,
It's Uses And related works
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Morphological Operators in Perceptrons
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Morphological Operators in Deep Networks
Morphological Features
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Notation
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Operator Definitions
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Alternate Sequential Filters (ASF)
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Morphological back-propagation
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Morphological layers
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Initialization
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Morphological Pooling layers
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Morphological learned descriptor layer
It's Real Life Experiments In Deep Learning
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Image classification with morphological pooling
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Image Denoising
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Edge detection