Titlebook: Document Analysis and Recognition – ICDAR 2024 Workshops; Athens, Greece, Augu Harold Mouchère,Anna Zhu Conference proceedings 2024 The Edi

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dithiolethione

aditional methods often falter with variable document types, leading to poor performance. To overcome these limitations, this paper introduces a text-graphic layer separation approach that enhances domain adaptability in document image restoration (DIR) systems. We propose ., which utilizes two laye

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nctioning as dynamic information and knowledge hubs, through the production, management and availability of open diachronic and synchronic data; in this light, this paper presents the Hellenic Parliament Library experience, focusing on a subcategory of historical parliamentary data, included in the

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–1977) in the Hellenic Parliament. A collaborative pilot project involving parliament, academia, and a research center facilitated the conversion of printed material to open data. The main tasks of the project include capturing digital images, a custom Optical Character Recognition (OCR) software so

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of visual storytelling across decades. Comic image segmentation is a pivotal aspect in the digital transformation of comics. Leveraging heuristic approaches, neural network-based model (YOLO), and innovative transformer-based architectures (GroundingDINO, SAM), our research aims to autonomously seg

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arch on comics has evolved from basic object detection to more sophisticated tasks. However, the field faces persistent challenges such as small datasets, inconsistent annotations, inaccessible model weights, and results that cannot be directly compared due to varying train/test splits and metrics.