Dr. Giuseppe De Gregorio
Assistent / PostDoc
Philosophisch-Historische Fakultät
Departement Altertumswissenschaften
Professur Marthot-Santaniello

Assistent / PostDoc

Petersgraben 51
4051 Basel
Schweiz

giuseppe.degregorio@unibas.ch

  • Artificial Intelligence (AI)
  • Developing and implementing innovative algorithms for handwriting recognition for historical documents

Employment History

October 2023 -PostDoc
Project "EGRAPSA: Retracing the evolutions of handwritings in Greco-Roman Egypt thanks to digital palaeography"
Department of Ancient Civilizations of the University of Basel
November 2022 – February 2023Research Grant
“Few-Shot learning techniques for the elaboration of handwritten documents of historical interest”
DIEM Department, University of Salerno, Fisciano Italy.
January 2022 – June 2022Research Grant
“Support tools for the transcription of handwritten documents of historical-cultural interest”
DIEM Department, University of Salerno, Fisciano Italy.
June 2021 – December 2022Research Grant
“Support tools for the transcription of handwritten documents of historical-cultural interest”
DIEM Department, University of Salerno, Fisciano Italy.
February 2020 – March 2020Research Grant
“Support tools for the transcription of handwritten documents of historical-cultural interest”
DIEM Department, University of Salerno, Fisciano Italy.

 

Academic Education

December 2019 – March 2023Ph.D. in Information Engineering
DIEM Department, University of Salerno, Fisciano Italy.
Specific field of the degree course: Ingegneria dell’Infromazione ING-INF/05
Thesis Title: N-gram Retrieval for Word Spotting in Historical Handwritten Collections
September 2016 – April 1019Master’s Degree in Computer Enginering
DIEM Department, University of Salerno, Fisciano Italy.
Specific field of the degree course: Ingegneria Informatica LM-32
2nd level degree in Computer Engineering
Thesis Title: Early Diagnosis for Neurodegenerative diseases from Handwriting Analysis: AI-based Approach
September 2008 – April 1015Bachelor’s Degree in Computer Enginering
DIEM Department, University of Salerno, Fisciano Italy.
Specific field of the degree course: Ingegneria Informatica L-8
1st level degree in Computer Engineering
Thesis Title: Un Linguaggio per la Descrizione di Modelli Fiscali (A Language for the Description of Tax Models)

 

Studies and Experiences Abroad

January 2022 – June 2022Computer Vision Center (CVC) - Universitad Autònoma de Barcelona, Spain

Journal Article

  • Journal of Imaging
    2023
    De Gregorio, G., Capriolo, G., & Marcelli, A. (2023). End-to-End Transcript Alignment of 17th Century Manuscripts: The Case of Moccia Code. Journal of Imaging, 9(1), 17.
    https://doi.org/10.3390/jimaging9010017
  • Engineering Applications of Artificial Intelligence
    2022
    Nicole D. Cilia, Giuseppe De Gregorio, Claudio De Stefano, Francesco Fontanella, Angelo Marcelli, Antonio Parziale, Diagnosing Alzheimer’s disease from on-line handwriting: A novel dataset and performance benchmarking, Engineering Applications of Artificial Intelligence, Volume 111, 2022
  • Journal of Imaging
    2021
    Marcelli, A., De Gregorio, G., & Santoro, A. (2020). A Model for Evaluating the Performance of a Multiple Keywords Spotting System for the Transcription of Historical Handwritten Documents. Journal of Imaging, 6(11), 117.
    https://doi.org/10.3390/jimaging6110117

Conference Proceedings

  • International Conference on Frontiers in Handwriting Recognition (ICFHR)
    2022
    De Gregorio, G., Biswas, S., Souibgui, M. A., Bensalah, A., Lladós, J., Fornés, A., & Marcelli, A. (2022, November). A Few Shot Multi-Representation Approach for N-Gram Spotting in Historical Manuscripts. In Frontiers in Handwriting Recognition: 18th International Conference, ICFHR 2022, Hyderabad, India, December 4–7, 2022, Proceedings (pp. 3-17). Cham: Springer International Publishing.
  • International Conference of the Italian Association for Artificial Intelligence
    2022
    De Gregorio, Giuseppe, and Angelo Marcelli. Word Spotting in Handwritten Historical Documents by N-gram Retrieval. In International Conference of the Italian Association for Artificial Intelligence, Udine, Italy,
  • International Conference on Frontiers in Handwriting Recognition (ICFHR)
    2022
    De Gregorio, Giuseppe, Ilaria Citro, and Angelo Marcelli. Transcript Alignment for Historical Handwritten Documents: The MiM Algorithm. Intertwining Graphonomics with Human Movements: 20th International Conference of the International Graphonomics Society, IGS 2021, Las Palmas de Gran Canaria, Spain, June 7-9, 2022, Proceedings. Cham: Springer International Publishing, 2022.
  • EvoStar 2022
    2022
    De Gregorio, Giuseppe, Antonio Della Cioppa, and Angelo Marcelli. Negative selection algorithm for alzheimer’s diagnosis: Design and performance evaluation. Applications of Evolutionary Computation: 25th European Conference, EvoApplications 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20–22, 2022, Proceedings. Cham: Springer International Publishing, 2022.
  • ICPR International Workshop: Artificial Intelligence for Healthcare Applications – AIHA2020
    2021
    De Gregorio, Giuseppe, Desiato, Domenico, Marcelli, Angelo, Polese, Giuseppe. A multi classifier approach for supporting Alzheimer’s diagnosis based on handwriting analysis.Pattern Recognition. ICPR International Workshops and Challenges: Virtual Event, January 10–15, 2021, Proceedings, Part I. Springer International Publishing, 2021.
  • ICFHR 2022: International Conference on Frontiers in Handwriting Recognition Hyderabad, India
    4 December 2022 – 7 December 2022
    At the conference, I presented the work 'Few Shot Multi-Representation N-gram Spotting for Historical Manuscripts'. Performance in retrieving words in historical documents is moderate. This is mainly due to the paucity of labelled data to train the models. In the paper, we propose a few-stroke learning paradigm for detecting sequences of a few characters in images of handwritten text that requires a small amount of labelled training data.
  • AIxIA 2022: 21st International Conference of the Italian Association for Artificial Intelligence
    Udine, Italy
    28 November 2022 – 2 December 2022
    At the conference, I presented the work 'Word Spotting in Handwritten Historical Documents by N-gram Retrieval'. The contribution deals with the problem of recovering handwritten words in images of documents belonging to small collections of historical interest. The proposed methodology focuses the search on sequences of characters instead of whole words, with the aim of making unknown words searchable by the system.
  • IGS 2021: The 20th Conference of the International Graphonomics Society
    Las Palmas de Gran Canaria, Spain
    7 June 2022 – 9 June 2022
    At the conference, I presented the work 'Transcript Alignment for Historical Handwritten Documents: The MiM Algorithm'. Tracing the image portion of a document that contains the handwritten text starting from the transcription is essential for the study as well as for the development of modern technologies that facilitate searching, indexing, and transcription. We have proposed a method to automatically align the transcript to images of handwritten words.
  • EvoStar 2022
    Madrid, Spain
    20 April 2022 – 22 April 2022
    At the conference, I presented the work 'Negative Selection Algorithm for Alzheimer's Diagnosis: Design and Performance Evaluation'. In the article, we present a method to discriminate between healthy subjects and Alzheimer's patients by analysing online writing. The methodology adapts a Negative Selection algorithm for the purpose and the idea is to use only information relating to the control group of healthy subjects in the learning phase.
  • ICPR International Workshop:
    Artificial Intelligence for Healthcare Applications – AIHA2020
    Milan, Italy
    10 January 2021
    At the conference, I presented the paper 'A Multi Classifier Approach for Supporting Alzheimer's Diagnosis Based on Handwriting Analysis'. The work presents an AI-based methodology that analyses handwriting and drawing tasks to discriminate between healthy subjects and patients affected by Alzheimer's disease. The use of AI favours the development of reliable, non-invasive, easy-to-use and inexpensive diagnostic tools.