Gabriele Cavallaro


  • Cloud Deep Networks for Hyperspectral Image Analysis
  • Parallel SVM for the analysis of hyperspectral data
  • A comparison of self-dual attribute profiles based on different filter rules for classification
  • Automatic framework for spectral--spatial classification based on supervised feature extraction and morphological attribute profiles
  • Automatic threshold selection for profiles of attribute filters based on granulometric characteristic functions
  • An advanced classifier for the joint use of LiDAR and hyperspectral data: Case study in Queensland, Australia
  • Classification Techniques in Remote Sensing Research using Smart Data Analytics
  • Smart data analytics methods for remote sensing applications
  • Smart Data Analytics Methods for Remote Sensing Applications
  • Extended Self-Dual Attribute Profiles for the Classification of Hyperspectral Images
  • On scalable data mining techniques for earth science
  • Processing high resolution images of urban areas with self-dual attribute filters
  • Remote sensing image classification using attribute filters defined over the tree of shapes
  • Spectral-Spatial Classification of Remote Sensing Optical Data with Morphological Attribute Profiles using Parallel and Scalable Methods
  • Region-based classification of remote sensing images with the morphological tree of shapes
  • Remote Sensing Image Classification Using Attribute Filters Defined over the Tree of Shapes
  • Unsupervised change detection analysis to multi-channel scenario based on morphological contextual analysis
  • On parallel and scalable classification and clustering techniques for earth science datasets
  • Automatic attribute profiles
  • Volcanic systems and fissure swarm and fracture database
  • Integration of LiDAR and Hyperspectral Data for Land-cover Classification: A Case Study
  • Scaling Support Vector Machines Towards Exascale Computing for Classification of Large-Scale High-Resolution Remote Sensing Images
  • The influence of sampling methods on pixel-wise hyperspectral image classification with 3d convolutional neural networks
  • High Performance and Cloud Computing for Remote Sensing Data
  • Automating Physical and Machine Learning Models using Scientific Workflows
  • Cloud deep networks for hyperspectral image analysis
  • Remote Sensing Data Analytics with the Udocker Container Tool using Multi-GPU Deep Learning Systems
  • Parallel and Scalable Machine Learning
  • Remote Sensing Big Data Classification with High Performance Distributed Deep Learning
  • On Understanding Big Impacts in Remotely Sensed Classification Using Support Vector Machine Methods
  • Facilitating efficient data analysis of remotely sensed images using standards-based parameter sweep models
  • Scalable Workflows for Remote Sensing Data Processing with the Deep-Est Modular Supercomputing Architecture
  • Multi-Scale Convolutional SVM Networks for Multi-Class Classification Problems of Remote Sensing Images
  • Detection of hedges based on attribute filters
  • On understanding big data impacts in remotely sensed image classification using support vector machine methods
  • Automatic morphological attribute profiles
  • Scalable developments for big data analytics in remote sensing
  • Remote sensing data fusion: Markov models and mathematical morphology for multisensor, multiresolution, and multiscale image classification
  • Tree-based supervised feature extraction method based on self-dual attribute profiles
  • Parallel computation of component trees on distributed memory machines
  • Modular supercomputing design supporting machine learning applications
  • Scaling DBSCAN towards exascale computing for clustering of big data sets
  • Automated Analysis of remotely sensed images using the UNICORE workflow management system
  • On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods
  • Remote Sensing Big Data Classification with High Performance Distributed Deep Learning

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