Pages that link to "Item:Q2189383"
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The following pages link to Max-plus operators applied to filter selection and model pruning in neural networks (Q2189383):
Displaying 10 items.
- Approximating morphological operators with part-based representations learned by asymmetric auto-encoders (Q1980892) (← links)
- Some open questions on morphological operators and representations in the deep learning era. A personal vision (Q2061783) (← links)
- On some associations between mathematical morphology and artificial intelligence (Q2061838) (← links)
- Going beyond p-convolutions to learn grayscale morphological operators (Q2061840) (← links)
- Sparse approximate solutions to max-plus equations (Q2061850) (← links)
- Toward a sparsity theory on weighted lattices (Q2678919) (← links)
- Learning grayscale mathematical morphology with smooth morphological layers (Q2678921) (← links)
- Learnable Empirical Mode Decomposition based on Mathematical Morphology (Q5024378) (← links)
- MorphoActivation: generalizing ReLU activation function by mathematical morphology (Q6103070) (← links)
- Logarithmic morphological neural nets robust to lighting variations (Q6103072) (← links)
