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U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts
Document Layout Analysis, which is the task of identifying different semantic regions inside of a document page, is a subject of great interest for both computer scientists and humanities scholars as it represents a fundamental step towards further analysis tasks for the former and a powerful tool to improve and facilitate the study of the documents for the latter.
Efficient few-shot learning for pixel-precise handwritten document layout analysis
Layout analysis is a task of uttermost importance in ancient handwritten document analysis and represents a fundamental step toward the simplification of subsequent tasks such as optical character recognition and automatic transcription.
Masked Transformer for image Anomaly Localization
Image anomaly detection consists in detecting images or image portions that are visually different from the majority of the samples in a dataset.
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