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Found 6 papers, 4 papers with code
Neural network scoring for efficient computing
One of the main applications and novelties is the measurement of algorithmic power efficiency.
Theory and Implementation of Complex-Valued Neural Networks
This work explains in detail the theory behind Complex-Valued Neural Network (CVNN), including Wirtinger calculus, complex backpropagation, and basic modules such as complex layers, complex activation functions, or complex weight initialization.
Impact of PolSAR pre-processing and balancing methods on complex-valued neural networks segmentation tasks
In this paper, we investigated the semantic segmentation of Polarimetric Synthetic Aperture Radar (PolSAR) using Complex-Valued Neural Network (CVNN).
Deep Learning-Based Anomaly Detection in Synthetic Aperture Radar Imaging
Experiments are performed to show the advantages of our method compared to the conventional Reed-Xiaoli algorithm, highlighting the importance of an efficient despeckling pre-processing step.
Riemannian optimization for non-centered mixture of scaled Gaussian distributions
The proposed Riemannian gradient descent algorithm is leveraged to solve this second minimization problem.
Robust Geometric Metric Learning
This paper proposes new algorithms for the metric learning problem.
