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Found 7 papers, 0 papers with code
Vital Records: Uncover the past from historical handwritten records
We present Vital Records, a demonstrator based on deep-learning approaches to handwritten-text recognition, table processing and information extraction, which enables data from century-old documents to be parsed and analysed, making it possible to explore death records in space and time.
LayoutXLM vs. GNN: An Empirical Evaluation of Relation Extraction for Documents
This paper investigates the Relation Extraction task in documents by benchmarking two different neural network models: a multi-modal language model (LayoutXLM) and a Graph Neural Network: Edge Convolution Network (ECN).
Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
We share a French-English parallel corpus of Foursquare restaurant reviews (https://europe. naverlabs. com/research/natural-language-processing/machine-translation-of-restaurant-reviews), and define a new task to encourage research on Neural Machine Translation robustness and domain adaptation, in a real-world scenario where better-quality MT would be greatly beneficial.
Comparing Machine Learning Approaches for Table Recognition in Historical Register Books
We present in this paper experiments on Table Recognition in hand-written registry books.
Bench-Marking Information Extraction in Semi-Structured Historical Handwritten Records
In this report, we present our findings from benchmarking experiments for information extraction on historical handwritten marriage records Esposalles from IEHHR - ICDAR 2017 robust reading competition.
Joint Structured Learning and Predictions under Logical Constraints in Conditional Random Fields
This paper is concerned with structured machine learning, in a supervised machine learning context.
