Contact

Dr.-Ing. Claudio Persello

Adresse: Spemannstr. 38
72076 Tübingen
Raum Nummer: 226
Tel.: 07071 601 542
Fax: 07071 601 552
E-Mail: claudio.persello

 

Bild von Persello, Claudio, Dr.-Ing.

Claudio Persello

Position: Postdoc  Abteilung: 

1.    EDUCATION

  • Ph.D. degree in “Information and Communication Technologies”, University of Trento, March 2010.
  • Master degree in Telecommunication Engineering from the University of Trento, final grade 110/110, July 2005.
  • Bachelor Degree in Telecommunication Engineering from the University of Trento, final grade 110/110, February 2003.
  • Technical Diploma from “Istituto Tecnico Industriale G. Galilei”, Bolzano, final grade 100/100, June 1999.


2.    PROFESSIONAL EXPERIENCES

  • SERVIZI S.T. S.R.L., Manager of a project for the development of a web application in GNU/Linux, 02/11/2005 - 30/10/2006
  • EUROPEAN SPACE RESEARCH INSTITUTE (ESRIN), Italian branch of the European Space Agency, Frascati (Roma), October 2002 – December 2002.


3.    TEACHING AND ACADEMIC ACTIVITY

  • Co-supervisor of several Bachelor and Master theses in Communication Engineering – University of Trento (from 2006 to 2010).
  • Co-supervisor of visiting students within the project “Advanced techniques for remote sensing image processing and recognition” (ITPAR – India-Trento Program for Advanced Research) phase 2 [2008-2013];
  • Teaching Assistant of the course “Sistemi di Telerilevamento” (Remote Sensing Systems) – Bachelor degree in Telecommunications Engineering – University of Trento (2008/09, 2009/10 and 2010/11).
  • Teacher of a seminar entitled “Introduzione ai sistemi di telerilevamento” (Introduction to Remote Sensing Systems) for the students of the course of Hydrology – bachelor degree in Environmental Engineering (December 2008).
  • Teaching assistant of the course “Laboratorio di Sistemi di Telerilevamento” (Laboratory of Remote Sensing Systems) – Bachelor degree in Telecommunications Engineering – University of Trento (2006/07 and 2007/08).


4.    SCIENTIFIC ACTIVITY
4.1 Research Interests

  • Analysis of the last generation of remote sensing images, in particular: very high resolution (VHR) and hyperspectral images.
  • Classification of remote sensing images with machine learning techniques (e.g., support vector machines).
  • Kernel methods for supervised, semisupervised learning and active learning.
  • Transfer learning and domain adaptation problems.
  • Selection of robust features for transfer learning problems.
  • Classification of remote sensing images when the available training set is not fully reliable.
  • Accuracy assessment in the classification of VHR images.
  • Estimation of forest structure and biomass from LIDAR Data.


4.2 Scientific Reviewer

  • IEEE Transactions on Geoscience and Remote Sensing;
  • IEEE Geoscience and Remote Sensing Letters;
  • IEEE Journal of Selected Topics in Signal Processing,
  • IEEE Journal of Selected Topics in Earth Observations and Remote Sensing;
  • Canadian Journal of Remote Sensing,
  • Pattern Recognition Letters;
  • IEEE International Geoscience and Remote Sensing Symposium (IGARSS).


4.3 Roles in organization of Conferences and workshops

  • Member of the Scientific Committee of the 6th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images (Multi Temp 2011),  Trento, Italy, 12-14 July 2011.

 

5. HONORS AND AWARDS

  • Awarded with the prize for the best PhD Thesis on Pattern Recognition published in 2012 by the GIRPR, which is the Italian branch of the International Association for Pattern Recognition (IAPR). The title of the thesis is "Advanced Techniques for the Classification of Very High Resolution and Hyperspectral Remote Sensing Images"

Präferenzen: 
Referenzen pro Seite: Jahr: Medium:

  
Zeige Zusammenfassung

Artikel (6):

Demir B, Persello C und Bruzzone L (März-2011) Batch-Mode Active-Learning Methods for the Interactive Classification of Remote Sensing Images IEEE Transactions on Geoscience and Remote Sensing 49(3) 1014-1031.
Persello C und Bruzzone L (März-2010) A Novel Protocol for Accuracy Assessment in Classification of Very High Resolution Images IEEE Transactions on Geoscience and Remote Sensing 48(3) 1232-1244.
Bruzzone L und Persello C (September-2009) A Novel Approach to the Selection of Spatially Invariant Features for the Classification of Hyperspectral Images with Improved Generalization Capability IEEE Transactions on Geoscience and Remote Sensing 47(9) 3180-3191.
Bruzzone L und Persello C (Juli-2009) A Novel Context-Sensitive Semisupervised SVM Classifier Robust to Mislabeled Training Samples IEEE Transactions on Geoscience and Remote Sensing 47(7) 2142-2154.
Soldati N, Robinson S, Persello C, Jovicich J und Bruzzone L (Januar-2009) Automatic classification of brain resting states using fMRI temporal signals Electronics Letters 45(1) 19-21.
Arnoldi E, Bruzzone L, Carlin L, Pedron L und Persello C (2007) Classificazione di immagini telerilevate satellitari per agricoltura di precisione MondoGis: Il Mondo dei Sistemi Informativi Geografici 63 13-17.

Beiträge zu Tagungsbänden (9):

Persello C und Bruzzone L (September-2011) Active Versus Semi-supervised Learning Paradigm for the Classification of Remote Sensing Images, Image and Signal Processing for Remote Sensing XVII, SPIE, Bellingham, WA, USA, 1-15, Series: Proceedings of the SPIE ; 8180.
Persello C und Bruzzone L (Juli-2011) A Novel Active Learning Strategy for Domain Adaptation in the Classification of Remote Sensing Images, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2011), IEEE, Piscataway, NJ, USA, 3720-3723.
Bruzzone L und Persello C (Juli-2010) Recent trends in classification of remote sensing data: active and semisupervised machine learning paradigms, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2010), IEEE, Piscataway, NJ, USA, 3720-3723.
Persello C und Bruzzone L (Juli-2009) A novel approach to the selection of spatially invariant features for classification of hyperspectral images, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2009), IEEE, Piscataway, NJ, USA, II-61-II-64.
Bruzzone L und Persello C (Juli-2009) Active learning for classification of remote sensing images, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2009), IEEE, Piscataway, NJ, USA, III-693-III-696.
Bruzzone L und Persello C (Juli-2008) A Novel Approach to the Selection of Robust and Invariant Features for Classification of Hyperspectral Images, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2008), IEEE, Piscataway, NJ, USA, I-66-I-69.
Bruzzone L und Persello C (Juli-2008) A Novel Protocol for Accuracy Assessment in Classification of Very High Resolution Multispectral and SAR Images, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2008), IEEE, Piscataway, NJ, USA, II-265-II-268.
Arnoldi E, Bruzzone L, Carlin L, Pedron L und Persello C (November-2007) Sistema avanzato per la classificazione delle aree agricole in immagini ad elevata risoluzione geometrica: applicazione al territorio del Trentino, 11. Conferenza Nazionale ASITA, 1-6.
pdf
Bruzzone L, Marconcini M und Persello C (Juli-2007) Fusion of spectral and spatial information by a novel SVM classification technique, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007), IEEE, Piscataway, NJ, USA, 4838-4841.

Beiträge zu Büchern (2):

Bruzzone L, Persello C und Demir B: Active Learning Methods in Classification of Remote Sensing Images, 303–324. In: Signal and Image Processing for Remote Sensing, (Ed) C.H. Chen, CRC Press, Hoboken, NJ, USA, (2012).
Bruzzone L und Persello C: Approaches Based on Support Vector Machine to Classification of Remote Sensing Data, 329-352. In: Handbook of Pattern Recognition and Computer Vision, (Ed) C.H. Chen, ICP, London, UK, (2010).

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Last updated: Montag, 22.05.2017