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Deep Segmentation of Corrupted Glyphs - ACM Digital Library
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由 G Melnik 著作2022被引用 7 次 — In this work, we introduce a deep neural network that computes character segmentation in palimpsests and petroglyphs while overcoming occlusions, missing parts ...
有關 Deep Segmentation of Corrupted Glyphs. 的學術文章 | |
Deep segmentation of corrupted glyphs - Melnik - 7 個引述 Ancient Egyptian hieroglyphs segmentation and … - Barucci - 10 個引述 … hieroglyphs segmentation with convolutional neural … - Guidi - 14 個引述 |
Deep Segmentation of Corrupted Glyphs
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In this work, we focus on the task of recovering characters and symbols from images of corrupted archaeological artifacts where data is partially erased, ...
Deep Segmentation of Corrupted Glyphs
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In this work, we focus on the task of recovering characters and symbols from images of corrupted archaeological artifacts where data is partially erased, ...
Deep Segmentation of Corrupted Glyphs
אוניברסיטת בן-גוריון
https://cris.bgu.ac.il › publications › dee...
אוניברסיטת בן-גוריון
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由 G Melnik 著作2022被引用 7 次 — Historical documents and archaeological artifacts are hard to process due to natural degradation, fading, spills, tears, overlaid data,, ...
Deep Segmentation of Corrupted Glyphs – Fingerprint
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Dive into the research topics of 'Deep Segmentation of Corrupted Glyphs'. Together they form a unique fingerprint. Sort by; Weight ...
DECOUPLING LAYOUT FROM GLYPH
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Deep imitator: handwriting calligraphy imitation via deep attention networks. ... corrupted data. This process, known as the reverse denoising process aims ...
Decoupling Layout from Glyph in Online Chinese ...
arXiv
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2024年10月4日 — An approach for handwritten chinese text recognition unifying character segmentation and recognition. Pattern Recognition, pp. 110373, 2024.
Evaluating Shape Representations for Maya Glyph ...
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2024年10月22日 — Shape representations are critical for visual analysis of cultural heritage materials. This article studies two types of shape ...
Ancient Egyptian Hieroglyphs Segmentation and ...
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The ancient hieroglyphs segmentation was faced in parallel, using a deep neural network architecture known as Mask-RCNN. This network was trained to segment the ...