4 papers
Ghost Features and Spooky Transfer Learning for Hypercomplex-Valued Neural Networks
Guilherme Vieira Neto, Marcos Eduardo Valle
Hypercomplex numbers extend the concept of complex numbers by introducing additional imaginary components. Besides increasing dimensionality, operations on the imaginary parts prov…
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…
Novel Complex-Valued Hopfield Neural Networks with Phase and Magnitude Quantization
Garimella Ramamurthy, Marcos Eduardo Valle, Tata Jagannadha Swamy
This research paper introduces two novel complex-valued Hopfield neural networks (CvHNNs) that incorporate phase and magnitude quantization. The first CvHNN employs a ceiling-type…
V-EfficientNets: Vector-Valued Efficiently Scaled Convolutional Neural Network Models
Guilherme Vieira Neto, Marcos Eduardo Valle
EfficientNet models are convolutional neural networks optimized for parameter allocation by jointly balancing network width, depth, and resolution. Renowned for their exceptional a…