Titlebook: Document Analysis and Recognition – ICDAR 2021 Workshops; Lausanne, Switzerlan Elisa H. Barney Smith,Umapada Pal Conference proceedings 202

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Transmedia Storytelling and the Apocalypsea graph representation of the extracted circuit components. The graph structure is then analysed using graph convolutional neural networks and node degree comparison to identify graph anomalies potentially resulting from false negatives from the object recognition module. Anomaly predictions are the

UTTER

Umar Hakim Mohd Hasri,Md Azalanshah Md Syed exhibits robust performance while being drastically smaller in size compared to strong baselines. Our annotated dataset and models represent a useful first step towards the development of focused systems for medical document image analytics, a domain that mandates robust systems for reliable inform

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Umar Hakim Mohd Hasri,Md Azalanshah Md Syedt with the stylus, thus the prior knowledge of the written word will drive the engine analysis. The second one relies on a single input: the child handwritten strokes. To drive the analysis, the strategy consists in generating hypotheses that are phonetically similar to the dictated instruction, whi

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Document Analysis and Recognition – ICDAR 2021 Workshops978-3-030-86198-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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978-3-030-86197-1Springer Nature Switzerland AG 2021

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Karen E. Sutherland,Richie BarkerLaTeX-based sequence represents the 2D structure of an HME as a 1D sequence. Consequently, the LaTeX-based sequence becomes longer, and HME recognition systems have difficulty in extracting its 2D structure. We propose a new representation for HMEs according to the relations of symbols, which shorte