Skip to main content

Research Repository

Advanced Search

All Outputs (27)

Digital interpretation of sensor-equipment diagrams. (2018)
Conference Proceeding
MORENO-GARCÍA, C.F. 2018. Digital interpretation of sensor-equipment diagrams. In Martin, K., Wiratunga, N. and Smith, L.S. (eds.) Proceedings of the 2018 Scottish Informatics and Computer Science Alliance (SCISA) workshop on reasoning, learning and explainability (ReaLX 2018), 27 June 2018, Aberdeen, UK. CEUR workshop proceedings, 2151. Aachen: CEUR-WS [online], session 2, paper 1. Available from: http://ceur-ws.org/Vol-2151/Paper_s2.pdf

A sensor-equipment diagram is a type of engineering drawing used in the industrial practice that depicts the interconnectivity between a group of sensors and a portion of an Oil & Gas facility. The interpretation of these documents is not a straightf... Read More about Digital interpretation of sensor-equipment diagrams..

Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings. (2017)
Conference Proceeding
MORENO-GARCÍA, C.F., ELYAN, E. and JAYNE, C. 2017. Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings. In Boracchi, G., Iliadis, L., Jayne, C. and Likas, A. (eds.) Engineering applications of neural networks: proceedings of the 18th International engineering applications of neural networks (EANN 2017), 25-27 August 2017, Athens, Greece. Communications in computer and information science, 744. Cham: Springer [online], pages 87-98. Available from: https://doi.org/10.1007/978-3-319-65172-9_8

The demand for digitisation of complex engineering drawings becomes increasingly important for the industry given the pressure to improve the efficiency and time effectiveness of operational processes. There have been numerous attempts to solve this... Read More about Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings..

An edit distance between graph correspondences. (2017)
Conference Proceeding
MORENO-GARCIA, C.F., SERRATOSA, F. and JIANG, X. 2017. An edit distance between graph correspondences. In Foggia, P., Liu, C.-L. and Vento, M (eds.) 2017. Graph-based representations in pattern recognition: proceedings of the 11th Image analysis in patter recognition technical committee 15th (IAPR-TC-15) international workshop (GbRPR 2017), 16-18 May 2017, Anacapri, Italy. Cham: Springer [online], pages 232-241. Available from: https://doi.org/10.1007/978-3-319-58961-9_21

The Hamming Distance has been largely used to calculate the dissimilarity of a pair of correspondences (also known as labellings or matchings) between two structures (i.e. sets of points, strings or graphs). Although it has the advantage of being sim... Read More about An edit distance between graph correspondences..

Generalised median of a set of correspondences based on the hamming distance. (2016)
Conference Proceeding
MORENO-GARCÍA, C.F., SERRATOSA, F. and CORTÉS, X. 2016. Generalised median of a set of correspondences based on the hamming distance. In: Robles-Kelly A., Loog M., Biggio B., Escolano F., Wilson R. (eds.) Structural, syntatic and statistical pattern recognition: proceedings of the 2016 Joint International Association of Pattern Recognition (IAPR) structural, syntatic and statistical pattern recognition international workshop (S+SSPR 2016), 29 November - 2 December 2016, Mérida, Mexico. Lecture Notes in Computer Science, vol 10029. Cham: Springer, pages 507-518. Available from: https://doi.org/10.1007/978-3-319-49055-7_45

A correspondence is a set of mappings that establishes a relation between the elements of two data structures (i.e. sets of points, strings, trees or graphs). If we consider several correspondences between the same two structures, one option to defin... Read More about Generalised median of a set of correspondences based on the hamming distance..

A graph repository for learning error-tolerant graph matching. (2016)
Conference Proceeding
MORENO-GARCÍA, C.F., CORTÉS, X. and SERRATOSA, F. 2016. A graph repository for learning error-tolerant graph matching. In Robles-Kelly, A., Loog, M., Biggio, B., Escolano, F. and Wilson, R. (eds.) Structural, syntactic and statistical pattern recognition: proceedings of 2016 Joint International Association of Pattern Recognition (IAPR) Structural and syntactic pattern recognition internaional workshops (SSPR 2016), and Statistical techniques in pattern recognition (SPR 2016) (S+SSPR 2016), 20 November - 2 December 2016, Mérida, Mexico. Lecture notes in computer science, 10029. Cham: Springer [online], pages 519-529. Available from: https://doi.org/10.1007/978-3-319-49055-7_46

In the last years, efforts in the pattern recognition field have been especially focused on developing systems that use graph based representations. To that aim, some graph repositories have been presented to test graph-matching algorithms or to lear... Read More about A graph repository for learning error-tolerant graph matching..

Semi-automatic pose estimation of a fleet of robots with embedded stereoscopic cameras. (2016)
Conference Proceeding
CORTÉS, X., SERRATOSA, F. and MORENO-GARCIA, C.-F. 2016. Semi-automatic pose estimation of a fleet of robots with embedded stereoscopic cameras. In Proceedings of 21st Institute of Electrical Electronic Engineers (IEEE) Emerging technologies and factory automation international conference 2016 (ETFA 2016), 6-9 September 2016, Berlin, Germany. Piscataway: IEEE [online], article ID 7733640. Available from: https://doi.org/10.1109/ETFA.2016.7733640

Given a fleet of robots, automatic estimation of the relative poses between them could be inaccurate in specific environments. We propose a framework composed by the fleet of robots with embedded stereoscopic cameras providing 2D and 3D images of the... Read More about Semi-automatic pose estimation of a fleet of robots with embedded stereoscopic cameras..

An interactive model for structural pattern recognition based on the Bayes classifier. (2015)
Conference Proceeding
CORTÉS, X., SERRATOSA, F. and MORENO-GARCÍA, C.F. 2015. An interactive model for structural pattern recognition based on the Bayes classifier. In De Marsico, M., Figueiredo, M. and Fred, A. (eds.) Proceedings of 4th International conference on pattern recognition applications and methods (ICPRAM 2015), 10-12 January 2015, Lisbon, Portugal, vol 1. Setubal: SCITEPRSS [online], pages 240-247. Available from: https://doi.org/10.5220/0005201602400247

This paper presents an interactive model for structural pattern recognition based on a naïve Bayes classifier. In some applications, the automatically computed correlation between local parts of two images is not good enough. Moreover, humans are ver... Read More about An interactive model for structural pattern recognition based on the Bayes classifier..