Publications

Unsupervised Segmentation of Hyperspectral Images Using 3-D Convolutional Autoencoders

Transfer Learning for Segmenting Dimensionally Reduced Hyperspectral Images

Benchmarking Deep Learning for On-Board Space Applications.

Antelope: Towards on-board anomaly detection in telemetry data using deep learning

Understanding the value of hyperspectral image super-resolution from Prisma data

Hyperspectral image pansharpening: the Prisma case study

Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 images

A real-world benchmark for Sentinel-2 multi-image super-resolution

Evaluating Hyperspectral Image Super-Resolution in Real-Life Scenarios

Semi-Simulated Training Data for Multi-Image Super-Resolution

Data Augmentation for Multi-Image Super-Resolution

Multiple-Image Super-Resolution Using Deep Learning and Statistical Features

Evaluating super-resolution of satellite images

Deep Learning for Multiple-Image Super-Resolution

Super-resolution reconstruction using deep learning: should we go deeper?

Deep learning for fast super-resolution reconstruction from multiple images

On Training Deep Networks for Satellite Image Super-Resolution

B4MultiSR: a benchmark for multiple-image super-resolution reconstruction.

Evaluating super-resolution reconstruction of satellite images.

Evolving imaging model for super-resolution reconstruction. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '18).

Towards evolutionary super-resolution.

Towards robust evaluation of super-resolution satellite image reconstruction.

Optimizing super-resolution reconstruction using a genetic algorithm