Fractional Laplacian Pyramids

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We develop a novel 2D functional learning framework that employs a sparsity-promoting regularization based on second-order derivatives. Motivated by the nature of the regularizer, we restrict the search space to the span of piecewise-linear box splines shi ...

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Fractional Laplacian Pyramids

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Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

From Human-Designed Convolutional Neural Networks Towards Robust Neural Architecture Search

Advances In Morphological Neural Networks: Training, Pruning And Enforcing Shape Constraints

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Vision-based Drone Flocking in Outdoor Environments

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Continuous-Domain Signal Reconstruction Using L-p-Norm Regularization

Systematic analysis of wavelet denoising methods for neural signal processing

A deep learning framework for matching of SAR and optical imagery

Functional Inverse Problems on Spheres: Theory, Algorithms and Applications

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