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ICPR 2024 Competition on Domain Adaptation and GEneralization for Character Classification (DAGECC)

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Pattern Recognition. Competitions (ICPR 2024)

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Abstract

In this companion paper for the DAGECC (Domain Adaptation and GEneralization for Character Classification) competition organized within the frame of the ICPR 2024 conference, we present the general context of the tasks we proposed to the community, we introduce the data that were prepared for the competition and we provide a summary of the results along with a description of the top three winning entries. The competition was centered around domain adaptation and generalization, and our core aim is to foster interest and facilitate advancement on these topics by providing a high-quality, lightweight, real world dataset able to support fast prototyping and validation of novel ideas.

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Notes

  1. 1.

    https://zenodo.org/records/13320997.

  2. 2.

    https://zenodo.org/records/11093441.

  3. 3.

    from \(18 \times 30\) pixels to \(86 \times 79\) pixels.

  4. 4.

    https://dagecc-challenge.github.io/icpr2024/.

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Acknowledgements

A special thank to SAFRAN, especially Basile Musquer (SAFRAN Aircraft Engines) and Thierry Arsaut (SAFRAN Helicopter Engines) for participating in the acquisition of the images, the creation of the dataset and for allowing the public release of the data. We are also grateful to Codabench, and specifically to Adrien Pavão, for their great support.

Author information

Authors and Affiliations

  1. Safran Tech, Digital Sciences and Technologies Department, Magny-Les-Hameaux, France

    Sofia Marino, Jennifer Vandoni & Ichraq Lemghari

  2. SATIE CNRS UMR 8029, Paris-Saclay University, Gif-sur-Yvette, France

    Emanuel Aldea, Ichraq Lemghari & Sylvie Le Hégarat-Mascle

  3. University of Caen Normandie, Caen, France

    Frédéric Jurie

Authors
  1. Sofia Marino
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  2. Jennifer Vandoni
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  3. Emanuel Aldea
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  4. Ichraq Lemghari
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  5. Sylvie Le Hégarat-Mascle
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  6. Frédéric Jurie
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Corresponding author

Correspondence to Jennifer Vandoni .

Editor information

Editors and Affiliations

  1. University of Salford, Salford, Lancashire, UK

    Apostolos Antonacopoulos

  2. Indian Institute of Technology Bombay, Mumbai, Maharashtra, India

    Subhasis Chaudhuri

  3. Johns Hopkins University, Baltimore, MD, USA

    Rama Chellappa

  4. Chinese Academy of Sciences, Beijing, China

    Cheng-Lin Liu

  5. IIT Kharagpur, Kharagpur, West Bengal, India

    Saumik Bhattacharya

  6. Indian Statistical Institute Kolkata, Kolkata, West Bengal, India

    Umapada Pal

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Marino, S., Vandoni, J., Aldea, E., Lemghari, I., Le Hégarat-Mascle, S., Jurie, F. (2025). ICPR 2024 Competition on Domain Adaptation and GEneralization for Character Classification (DAGECC). In: Antonacopoulos, A., Chaudhuri, S., Chellappa, R., Liu, CL., Bhattacharya, S., Pal, U. (eds) Pattern Recognition. Competitions. ICPR 2024. Lecture Notes in Computer Science, vol 15334. Springer, Cham. https://doi.org/10.1007/978-3-031-80139-6_12

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  • DOI: https://doi.org/10.1007/978-3-031-80139-6_12

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