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of 8
pro vyhledávání: '"Livathinos, Nikolaos"'
Autor:
Auer, Christoph, Lysak, Maksym, Nassar, Ahmed, Dolfi, Michele, Livathinos, Nikolaos, Vagenas, Panos, Ramis, Cesar Berrospi, Omenetti, Matteo, Lindlbauer, Fabian, Dinkla, Kasper, Mishra, Lokesh, Kim, Yusik, Gupta, Shubham, de Lima, Rafael Teixeira, Weber, Valery, Morin, Lucas, Meijer, Ingmar, Kuropiatnyk, Viktor, Staar, Peter W. J.
This technical report introduces Docling, an easy to use, self-contained, MIT-licensed open-source package for PDF document conversion. It is powered by state-of-the-art specialized AI models for layout analysis (DocLayNet) and table structure recogn
Externí odkaz:
http://arxiv.org/abs/2408.09869
Autor:
Naparstek, Oshri, Pony, Roi, Shapira, Inbar, Dahood, Foad Abo, Azulai, Ophir, Yaroker, Yevgeny, Rubinstein, Nadav, Lysak, Maksym, Staar, Peter, Nassar, Ahmed, Livathinos, Nikolaos, Auer, Christoph, Amrani, Elad, Friedman, Idan, Prince, Orit, Burshtein, Yevgeny, Goldfarb, Adi Raz, Barzelay, Udi
In recent years, the challenge of extracting information from business documents has emerged as a critical task, finding applications across numerous domains. This effort has attracted substantial interest from both industry and academy, highlighting
Externí odkaz:
http://arxiv.org/abs/2405.00505
Autor:
Mishra, Lokesh, Berrospi, Cesar, Dinkla, Kasper, Antognini, Diego, Fusco, Francesco, Bothur, Benedikt, Lysak, Maksym, Livathinos, Nikolaos, Nassar, Ahmed, Vagenas, Panagiotis, Morin, Lucas, Auer, Christoph, Dolfi, Michele, Staar, Peter
Publikováno v:
AAAI 2024, 38, 23814-23816
We present Deep Search DocQA. This application enables information extraction from documents via a question-answering conversational assistant. The system integrates several technologies from different AI disciplines consisting of document conversion
Externí odkaz:
http://arxiv.org/abs/2311.18481
Autor:
Auer, Christoph, Nassar, Ahmed, Lysak, Maksym, Dolfi, Michele, Livathinos, Nikolaos, Staar, Peter
Transforming documents into machine-processable representations is a challenging task due to their complex structures and variability in formats. Recovering the layout structure and content from PDF files or scanned material has remained a key proble
Externí odkaz:
http://arxiv.org/abs/2305.14962
Extracting tables from documents is a crucial task in any document conversion pipeline. Recently, transformer-based models have demonstrated that table-structure can be recognized with impressive accuracy using Image-to-Markup-Sequence (Im2Seq) appro
Externí odkaz:
http://arxiv.org/abs/2305.03393
Tables organize valuable content in a concise and compact representation. This content is extremely valuable for systems such as search engines, Knowledge Graph's, etc, since they enhance their predictive capabilities. Unfortunately, tables come in a
Externí odkaz:
http://arxiv.org/abs/2203.01017
Autor:
Livathinos, Nikolaos, Berrospi, Cesar, Lysak, Maksym, Kuropiatnyk, Viktor, Nassar, Ahmed, Carvalho, Andre, Dolfi, Michele, Auer, Christoph, Dinkla, Kasper, Staar, Peter
The number of published PDF documents has increased exponentially in recent decades. There is a growing need to make their rich content discoverable to information retrieval tools. In this paper, we present a novel approach to document structure reco
Externí odkaz:
http://arxiv.org/abs/2102.09395
Autor:
Livathinos, Nikolaos S.
One of the most widely used simulation environments for mobile wireless networks is the Network Simulator 2 (NS-2). However NS-2 stores its outcome in a text file, so there is a need for a visualization tool to animate the simulation of the wireless
Externí odkaz:
http://arxiv.org/abs/0902.4527