Designed Dithering Sign Activation for Binary Neural Networks

1 code implementation • 3 May 2024 • Brayan Monroy, Juan Estupiñan, Tatiana Gelvez-Barrera, Jorge Bacca, Henry Arguello

Binary Neural Networks emerged as a cost-effective and energy-efficient solution for computer vision tasks by binarizing either network weights or activations.

JR2net: A Joint Non-Linear Representation and Recovery Network for Compressive Spectral Imaging

1 code implementation • 16 May 2022 • Brayan Monroy, Jorge Bacca, Henry Arguello

Deep learning models are state-of-the-art in compressive spectral imaging (CSI) recovery.

Deep Low-Dimensional Spectral Image Representation for Compressive Spectral Reconstruction

1 code implementation • IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP) 2021 • Brayan Monroy, Jorge Bacca, Henry Arguello

This paper proposes an autoencoder-based network that guarantees a low-dimensional spectral representation through feature reduction, which can be used as prior in the compressive spectral imaging reconstruction.

Spectral Reconstruction