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Gabriele Cavallaro - Dósent

Gabriele Cavallaro

–

Verkfræði- og náttúruvísindasvið

Gabriele CavallaroHann/Hans

Dósent

Aðsetur
Utan H.Í.
Sími
5254694
Tölvupóstur
gcavallaro [hjá] hi.is

Starfseining
Rafmagns- og tölvuverkfræðideild

ORCID vefsíða
https://orcid.org/0000-0002-3239-9904
Rannsóknagátt – Gabriele Cavallaro

Show Útgefið efni

2025

Lossy Neural Compression for Geospatial AnalyticsIEEE Geoscience and Remote Sensing Magazine

2024

A CNN Architecture Tailored For Quantum Feature Map-Based Radar Sounder Signal Segmentation
A Hybrid Quantum-Classical CNN Architecture for Semantic Segmentation of Radar Sounder Data
Enhancing Land Cover Mapping
High Performance and Disruptive Computing in Remote SensingIEEE Geoscience and Remote Sensing Magazine
Local Binary and Multiclass SVMs Trained on a Quantum AnnealerIEEE Transactions on Quantum Engineering
Reverse Quantum Annealing for Hybrid Quantum-Classical Satellite Mission Planning
Sen4MapIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Supporting Seismic Data Survey Design Through the Integration of Satellite-Based Land Cover Maps
Vectorized Highly Parallel Density-based Clustering for Applications with NoiseIEEE Access

2023

Accuracy assessment of land-use-land-cover maps
A Summer School Session on Mastering Geospatial Artificial Intelligence: From Data Production to Artificial Intelligence Foundation Model Development and Downstream Applications [Technical Committees]IEEE Geoscience and Remote Sensing Magazine
Deep-Learning-Based 3-D Surface Reconstruction-A SurveyProceedings of the IEEE
Enhancing Distributed Neural Network Training Through Node-Based CommunicationsIEEE Transactions on Neural Networks and Learning Systems
FOREWORDGeoSearch 2023 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data

2022

High-Performance and Disruptive Computing in Remote SensingIEEE Geoscience and Remote Sensing Magazine
Learning from Data for Remote Sensing Image AnalysisInternational Journal of Remote Sensing
Optimizing Distributed Deep Learning in Heterogeneous Computing Platforms for Remote Sensing Data Classification
Remote Sensing Image Classification Using CNNs With Balanced Gradient for Distributed Heterogeneous ComputingIEEE Geoscience and Remote Sensing Letters

2021

FOREWORDProceedings of the 1st ACM SIGSPATIAL International Workshop on Searching and Mining Large Collections of Geospatial Data, GeoSearch 2021

2020

Super-Resolution of Large Volumes of Sentinel-2 Images with High Performance Distributed Deep Learning