3 papers
math.FA2026
Morphological Representation Theory in the Fourier Inf-Semilattice: Universal Decomposition of Frequency-Domain Deep Learning Operators
Gustavo, Angulo
We develop a morphological representation theory for operators acting in the frequency domain of . Equipping the space with the \emph{Fourier inf-semilattice} or…
cs.AI2026
Lattice theory and algebraic models for deep convolutional learning based on mathematical morphology
Gustavo, Angulo
We develop a rigorous algebraic framework for deep convolutional architectures, CNNs, ResNets, and encoder--decoder networks such as UNet, grounded in lattice theory and mathematic…
cs.CV2025
Approximating Condorcet Ordering for Vector-valued Mathematical Morphology
Marcos Eduardo Valle, Santiago Velasco-Forero, Joao Batista Florindo +1
Mathematical morphology provides a nonlinear framework for image and spatial data processing and analysis. Although there have been many successful applications of mathematical mor…