[visionlist] IJDAR Special issue - computer vision systems for document analysis and recognition

[Claudio Piciarelli]

[Apologies if you receive multiple copies]

Dear Colleagues,

We are pleased to announce a Special Issue of the International Journal on Document Analysis and Recognition (IJDAR) focused on Computer Vision Systems for Document Analysis and Recognition.

Submission website: https://link.springer.com/collections/jaeiejghgj

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Overview

This special issue focuses on advancing the state of the art in Document Analysis from a computer vision and AI perspective, with particular emphasis on robustness, generalization, and multimodality.
The aim is to bring together novel methodological and applied contributions that address document heterogeneity in terms of language, visual appearance, layout structure, writing styles, and semantic organization. We particularly encourage submissions that go beyond narrowly defined benchmarks and propose approaches capable of generalizing across document domains, formats, and acquisition conditions.

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Topics of Interest

Research papers are solicited in, but not limited to, the following areas:
* Robust document image analysis under varying layouts and writing styles
* Learning in low-data and low-resource language scenarios
* Multimodal document understanding combining visual, textual, and structural cues
* Cross-domain and cross-format generalization
* Analysis of historical and cultural heritage documents
* Self-supervised, few-shot, and transfer learning for document tasks
* Layout analysis, document structure understanding, and semantic modeling
* Integration of document analysis into real-world industrial and societal applications
By promoting cross-disciplinary interaction between computer vision, pattern recognition, NLP, digital humanities, and applied AI, this special issue aims to push document analysis toward more inclusive, generalizable, and practically deployable solutions.

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Important Date
* Submission deadline: September 20, 2026
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Guest Editors
* Axel De Nardin - AVML lab, University of Udine, Italy
* Silvia Zottin - AVML lab, University of Udine, Italy
* Claudio Piciarelli - AVML lab, University of Udine, Italy
* Gian Luca Foresti - AVML lab, University of Udine, Italy
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For additional information and submission guidelines, please visit the submission website above.
If you have any questions, feel free to contact the guest editors.
We look forward to your contributions.

Best regards,
The Guest Editors

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