Search Results for author: Antonio Jimeno Yepes

Found 38 papers, 7 papers with code

Using Discourse Structure to Differentiate Focus Entities from Background Entities in Scientific Literature

no code implementations ALTA 2021 Antonio Jimeno Yepes, Ameer Albahem, Karin Verspoor

In developing systems to identify focus entities in scientific literature, we face the problem of discriminating key entities of interest from other potentially relevant entities of the same type mentioned in the articles.

Hyperplane bounds for neural feature mappings

1 code implementation15 Jan 2022 Antonio Jimeno Yepes

Deep learning methods minimise the empirical risk using loss functions such as the cross entropy loss.

ICDAR 2021 Competition on Scientific Literature Parsing

3 code implementations8 Jun 2021 Antonio Jimeno Yepes, Xu Zhong, Douglas Burdick

Scientific literature contain important information related to cutting-edge innovations in diverse domains.

Natural Language Processing object-detection +2

Single versus Multiple Annotation for Named Entity Recognition of Mutations

1 code implementation19 Jan 2021 David Martinez Iraola, Antonio Jimeno Yepes

The focus of this paper is to address the knowledge acquisition bottleneck for Named Entity Recognition (NER) of mutations, by analysing different approaches to build manually-annotated data.

named-entity-recognition NER

Understanding in Artificial Intelligence

no code implementations17 Jan 2021 Stefan Maetschke, David Martinez Iraola, Pieter Barnard, Elaheh ShafieiBavani, Peter Zhong, Ying Xu, Antonio Jimeno Yepes

A question remains of how much understanding is leveraged by these methods and how appropriate are the current benchmarks to measure understanding capabilities.

Natural Language Understanding Question Answering +1

COVID-SEE: Scientific Evidence Explorer for COVID-19 Related Research

no code implementations18 Aug 2020 Karin Verspoor, Simon Šuster, Yulia Otmakhova, Shevon Mendis, Zenan Zhai, Biaoyan Fang, Jey Han Lau, Timothy Baldwin, Antonio Jimeno Yepes, David Martinez

We present COVID-SEE, a system for medical literature discovery based on the concept of information exploration, which builds on several distinct text analysis and natural language processing methods to structure and organise information in publications, and augments search by providing a visual overview supporting exploration of a collection to identify key articles of interest.

Natural Language Processing

Image-based table recognition: data, model, and evaluation

5 code implementations ECCV 2020 Xu Zhong, Elaheh ShafieiBavani, Antonio Jimeno Yepes

In addition, we propose a new Tree-Edit-Distance-based Similarity (TEDS) metric for table recognition, which more appropriately captures multi-hop cell misalignment and OCR errors than the pre-established metric.

Information Retrieval Optical Character Recognition +1

Global Locality in Biomedical Relation and Event Extraction

no code implementations WS 2020 Elaheh ShafieiBavani, Antonio Jimeno Yepes, Xu Zhong, David Martinez Iraola

Due to the exponential growth of biomedical literature, event and relation extraction are important tasks in biomedical text mining.

Event Extraction Relation Extraction

PubLayNet: largest dataset ever for document layout analysis

5 code implementations16 Aug 2019 Xu Zhong, Jianbin Tang, Antonio Jimeno Yepes

Deep neural networks that are developed for computer vision have been proven to be an effective method to analyze layout of document images.

Document Layout Analysis Transfer Learning

Findings of the WMT 2018 Biomedical Translation Shared Task: Evaluation on Medline test sets

no code implementations WS 2018 Mariana Neves, Antonio Jimeno Yepes, Aur{\'e}lie N{\'e}v{\'e}ol, Cristian Grozea, Amy Siu, Madeleine Kittner, Karin Verspoor

Machine translation enables the automatic translation of textual documents between languages and can facilitate access to information only available in a given language for non-speakers of this language, e. g. research results presented in scientific publications.

Machine Translation Translation

Improving classification accuracy of feedforward neural networks for spiking neuromorphic chips

no code implementations19 May 2017 Antonio Jimeno Yepes, Jianbin Tang, Benjamin Scott Mashford

We achieve this by training directly a binary hardware crossbar that accommodates the TrueNorth axon configuration constrains and we propose a different neuron model.

EEG General Classification

Knowledge-Based Biomedical Word Sense Disambiguation with Neural Concept Embeddings

no code implementations26 Oct 2016 A. K. M. Sabbir, Antonio Jimeno Yepes, Ramakanth Kavuluru

In this paper, we employ knowledge-based approaches that also exploit recent advances in neural word/concept embeddings to improve over the state-of-the-art in biomedical WSD using the MSH WSD dataset as the test set.

named-entity-recognition Named Entity Recognition +4

Improving energy efficiency and classification accuracy of neuromorphic chips by learning binary synaptic crossbars

no code implementations25 May 2016 Antonio Jimeno Yepes, Jianbin Tang

Previous work has achieved this by training a network to learn continuous probabilities and deployment to a neuromorphic architecture by random sampling these probabilities.

General Classification

The Scielo Corpus: a Parallel Corpus of Scientific Publications for Biomedicine

no code implementations LREC 2016 Mariana Neves, Antonio Jimeno Yepes, Aur{\'e}lie N{\'e}v{\'e}ol

We show that for all language pairs, a statistical machine translation system trained on the parallel corpora achieves performance that rivals or exceeds the state of the art in the biomedical domain.

Machine Translation Translation

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