Search Results for author: Roberto Arroyo

Found 5 papers, 0 papers with code

Key Information Extraction in Purchase Documents using Deep Learning and Rule-based Corrections

no code implementations PANDL (COLING) 2022 Roberto Arroyo, Javier Yebes, Elena Martínez, Héctor Corrales, Javier Lorenzo

We prove the enhancements provided by these rule-based corrections over the baseline DL results in the presented experiments for purchase documents from public and NielsenIQ datasets.

Key Information Extraction Line Detection +2

Multi-label classification of promotions in digital leaflets using textual and visual information

no code implementations EcomNLP (COLING) 2020 Roberto Arroyo, David Jiménez-Cabello, Javier Martínez-Cebrián

We demonstrate the effectiveness of our approach for two separated tasks: 1) image-based detection of the descriptions for each individual promotion and 2) multi-label classification of the product categories using the text from the product descriptions.

General Classification Multi-Label Classification +2

Integration of Text-maps in Convolutional Neural Networks for Region Detection among Different Textual Categories

no code implementations26 May 2019 Roberto Arroyo, Javier Tovar, Francisco J. Delgado, Emilio J. Almazán, Diego G. Serrador, Antonio Hurtado

Concretely, these words are previously extracted using Optical Character Recognition (OCR) and they are colored according to the probability of belonging to a textual category of interest.

Optical Character Recognition Optical Character Recognition (OCR)

Street-view change detection with deconvolutional networks

no code implementations Autonomous Robots 2018 Pablo F. Alcantarilla, Simon Stent, Germán Ros, Roberto Arroyo, Riccardo Gherardi

We propose a system for performing structural change detection in street-view videos captured by a vehicle-mounted monocular camera over time.

3D Reconstruction Change Detection +2

Can we unify monocular detectors for autonomous driving by using the pixel-wise semantic segmentation of CNNs?

no code implementations4 Jul 2016 Eduardo Romera, Luis M. Bergasa, Roberto Arroyo

Autonomous driving is a challenging topic that requires complex solutions in perception tasks such as recognition of road, lanes, traffic signs or lights, vehicles and pedestrians.

Autonomous Driving Image Segmentation +2

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