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Lorenzo Bruzzone

Lorenzo Bruzzone

Research.com Recognitions

  • 2010 - IEEE Fellow For contributions to pattern recognition and image processing for remote sensing

Overview

Lorenzo Bruzzone is affiliated with the University of Trento in Italy and has contributed extensively to the field of engineering, focusing particularly on remote sensing and image processing. Their research encompasses several interrelated subfields including media technology, astronomy and astrophysics, atmospheric science, computer vision and pattern recognition, and ecology.

Their work covers multiple main topics, emphasizing remote-sensing image classification, remote sensing and land use, and remote sensing in agriculture. Additional research interests include advanced image fusion techniques, planetary science and exploration, astro and planetary science, and advanced image and video retrieval techniques.

Lorenzo Bruzzone has a significant publication record in key venues such as:

  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • IEEE Geoscience and Remote Sensing Letters
  • arXiv (Cornell University)
  • IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Recent notable papers include:

  • "Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification" (2020), published in IEEE Transactions on Geoscience and Remote Sensing
  • "LANet: Local Attention Embedding to Improve the Semantic Segmentation of Remote Sensing Images" (2020), published in IEEE Transactions on Geoscience and Remote Sensing
  • "SemiCDNet: A Semisupervised Convolutional Neural Network for Change Detection in High Resolution Remote-Sensing Images" (2020), published in IEEE Transactions on Geoscience and Remote Sensing
  • "Bi-Temporal Semantic Reasoning for the Semantic Change Detection in HR Remote Sensing Images" (2022), published in IEEE Transactions on Geoscience and Remote Sensing
  • "Building Change Detection in VHR SAR Images via Unsupervised Deep Transcoding" (2020), published in IEEE Transactions on Geoscience and Remote Sensing

Frequent co-authors associated with their research include:

  • Francesca Bovolo
  • Leonardo Carrer
  • D Kunkee
  • John P. Kerekes
  • William J. Emery

Their academic recognition includes being named an IEEE Fellow in 2010 for contributions to pattern recognition and image processing for remote sensing.

Best Publications

  • Recent Advances in Techniques for Hyperspectral Image Processing

    Antonio Plaza;Jon Atli Benediktsson;Joseph W. Boardman;Jason Brazile

  • Automatic analysis of the difference image for unsupervised change detection

    L. Bruzzone;D.F. Prieto

  • An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images

    Y. Bazi;L. Bruzzone;F. Melgani

  • Morphological Attribute Profiles for the Analysis of Very High Resolution Images

    M Dalla Mura;J Atli Benediktsson;B Waske;L Bruzzone

  • Advances in Hyperspectral Image Classification: Earth Monitoring with Statistical Learning Methods

    Gustavo Camps-Valls;Devis Tuia;Lorenzo Bruzzone;Jon Atli Benediktsson

  • A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain

    F. Bovolo;L. Bruzzone

  • Earthquake Damage Assessment of Buildings Using VHR Optical and SAR Imagery

    Dominik Brunner;Guido Lemoine;Lorenzo Bruzzone

  • Image fusion techniques for remote sensing applications

    Giovanni Simone;Alfonso Farina;Francesco Carlo Morabito;Sebastiano B. Serpico

  • An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images

    L. Bruzzone;D.F. Prieto

  • A detail-preserving scale-driven approach to change detection in multitemporal SAR images

    F. Bovolo;L. Bruzzone

  • Extended profiles with morphological attribute filters for the analysis of hyperspectral data

    Mauro Dalla Mura;Jon Atli Benediktsson;Bjorn Waske;Lorenzo Bruzzone

  • A Split-Based Approach to Unsupervised Change Detection in Large-Size Multitemporal Images: Application to Tsunami-Damage Assessment

    F. Bovolo;L. Bruzzone

  • Supervised change detection in VHR images using contextual information and support vector machines

    Michele Volpi;Devis Tuia;Francesca Bovolo;Mikhail F. Kanevski

  • Semisupervised Transfer Component Analysis for Domain Adaptation in Remote Sensing Image Classification

    Giona Matasci;Michele Volpi;Mikhail Kanevski;Lorenzo Bruzzone

  • An advanced system for the automatic classification of multitemporal SAR images

    L. Bruzzone;M. Marconcini;U. Wegmuller;A. Wiesmann

  • Learning Spectral-Spatial-Temporal Features via a Recurrent Convolutional Neural Network for Change Detection in Multispectral Imagery

    Lichao Mou;Lorenzo Bruzzone;Xiao Xiang Zhu

  • Building Change Detection in Multitemporal Very High Resolution SAR Images

    Carlo Marin;Francesca Bovolo;Lorenzo Bruzzone

  • A Support Vector Domain Description Approach to Supervised Classification of Remote Sensing Images

    J. Munoz-Marf;L. Bruzzone;G. Camps-Vails

  • Building Height Retrieval From VHR SAR Imagery Based on an Iterative Simulation and Matching Technique

    D. Brunner;G. Lemoine;L. Bruzzone;H. Greidanus

  • Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity

    Yuanxin Ye;Jie Shan;Lorenzo Bruzzone;Li Shen

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