All Outputs (71)

Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. (2021)
Journal Article
MEDINA, E.C.G., ESPITIA, V.M.V., SILVA, D.C., DE LAS CUEVAS, S.F.R., HIRATA, M.P., CHEN, A.Z., GONZÁLEZ, J.A.G., BUSTAMANTE-BELLO, R. and MORENO-GARCÍA, C.F. 2021. Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems. Applied sciences [online], 11(7), article 2925. Available from: https://doi.org/10.3390/app11072925

Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional... Read More about Object detection, distributed cloud computing and parallelization techniques for autonomous driving systems..

An IoT based industry 4.0 architecture for integration of design and manufacturing systems. (2020)
Presentation / Conference Contribution
ANBALAGAN, A. and MORENO-GARCIA, C.F. 2021. An IoT based industry 4.0 architecture for integration of design and manufacturing systems. Materials today: proceedings [online], 46(17): proceedings of 3rd International conference on materials, manufacturing and modelling 2021 (ICMMM 2021), 19-21 March 2021, [virtual event], pages 7135-7142. Available from: https://doi.org/10.1016/j.matpr.2020.11.196

This paper proposes an Internet of Things (IoT) based 5-stage Industry 4.0 architecture to integrate the design and manufacturing systems in a Cyber Physical Environment (CPE). It considers the transfer of design and manufacturing systems data throug... Read More about An IoT based industry 4.0 architecture for integration of design and manufacturing systems..

A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols. (2020)
Presentation / Conference Contribution
RODRIGUEZ-TIRADO, A., MAGALLAN-RAMIREZ, D., MARTINEZ-AGUILAR, J.D., MORENO-GARCIA, C.F., BALDERAS, D. and LOPEZ-CAUDANA, E. 2020. A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols. In Proceedings of 13th Developments in eSystems engineering international conference 2020 (DeSe 2020), 13-17 December 2020, [virtual event]. Piscataway: IEEE [online], pages 152-157. Available from: https://doi.org/10.1109/DeSE51703.2020.9450731

Maze navigation is a recurring challenge in robotics competitions, where the aim is to design a strategy for one or several entities to traverse the optimal path in a fast and efficient way. To do so, numerous alternatives exist, relying on different... Read More about A pipeline framework for robot maze navigation using computer vision, path planning and communication protocols..

Assessing the clinicians’ pathway to embed artificial intelligence for assisted diagnostics of fracture detection. (2020)
Presentation / Conference Contribution
MORENO-GARCÍA, C.F., DANG, T., MARTIN, K., PATEL, M., THOMPSON, A., LEISHMAN, L. and WIRATUNGA, N. 2020. Assessing the clinicians’ pathway to embed artificial intelligence for assisted diagnostics of fracture detection. In Bach, K., Bunescu, R., Marling, C. and Wiratunga, N. (eds.) Knowledge discovery in healthcare data 2020: proceedings of the 5th Knowledge discovery in healthcare data international workshop 2020 (KDH 2020), co-located with 24th European Artificial intelligence conference (ECAI 2020), 29-30 August 2020, [virtual conference]. CEUR workshop proceedings, 2675. Aachen: CEUR-WS [online], pages 63-70. Available from: http://ceur-ws.org/Vol-2675/paper10.pdf

Fracture detection has been a long-standingparadigm on the medical imaging community. Many algo-rithms and systems have been presented to accurately detectand classify images in terms of the presence and absence offractures in different parts of the... Read More about Assessing the clinicians’ pathway to embed artificial intelligence for assisted diagnostics of fracture detection..

Deep learning for text detection and recognition in complex engineering diagrams. (2020)
Presentation / Conference Contribution
JAMIESON, L, MORENO-GARCIA, C.F. and ELYAN, E. 2020. Deep learning for text detection and recognition in complex engineering diagrams. In Proceedings of the 2020 Institute of Electrical and Electronics Engineers (IEEE) International joint conference on neural networks (IEEE IJCNN 2020), part of the 2020 IEEE World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 IEEE congress on evolutionary computation (IEEE CEC 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 19-24 July 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9207127. Available from: https://doi.org/10.1109/IJCNN48605.2020.9207127

Engineering drawings such as Piping and Instrumentation Diagrams contain a vast amount of text data which is essential to identify shapes, pipeline activities, tags, amongst others. These diagrams are often stored in undigitised format, such as paper... Read More about Deep learning for text detection and recognition in complex engineering diagrams..

Pixel-based layer segmentation of complex engineering drawings using convolutional neural networks. (2020)
Presentation / Conference Contribution
MORENO-GARCÍA, C.F., JOHNSTON, P. and GARKUWA, B. 2020. Pixel-based layer segmentation of complex engineering drawings using convolutional neural networks. In Proceedings of the 2020 Institute of Electrical and Electronics Engineers (IEEE) International joint conference on neural networks (IEEE IJCNN 2020), part of the 2020 IEEE World congress on computational intelligence (IEEE WCCI 2020) and co-located with the 2020 IEEE congress on evolutionary computation (IEEE CEC 2020) and the 2020 IEEE International fuzzy systems conference (FUZZ-IEEE 2020), 19-24 July 2020, [virtual conference]. Piscataway: IEEE [online], article ID 9207479. Available from: https://doi.org/10.1109/IJCNN48605.2020.9207479

One of the key features of most document image digitisation systems is the capability of discerning between the main components of the printed representation at hand. In the case of engineering drawings, such as circuit diagrams, telephone exchanges... Read More about Pixel-based layer segmentation of complex engineering drawings using convolutional neural networks..

CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification. (2020)
Journal Article
ELYAN, E., MORENO-GARCIA, C.F. and JAYNE, C. 2021. CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification. Neural computing and applications [online], 33(7), pages 2839-2851. Available from: https://doi.org/10.1007/s00521-020-05130-z

Class-imbalanced datasets are common across several domains such as health, banking, security, and others. The dominance of majority class instances (negative class) often results in biased learning models, and therefore, classifying such datasets re... Read More about CDSMOTE: class decomposition and synthetic minority class oversampling technique for imbalanced-data classification..

Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks. (2020)
Presentation / Conference Contribution
ELYAN, E., MORENO-GARCÍA, C.F. and JOHNSTON, P. 2020. Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks. In Iliadis, L., Angelov, P.P., Jayne, C. and Pimenidis, E. (eds.) Proceedings of the 21st Engineering applications of neural networks conference 2020 (EANN 2020); proceedings of the EANN 2020, 5-7 June 2020, Halkidiki, Greece. Proceedings of the International Neural Networks Society, 2. Cham: Springer [online], pages 215-224. Available from: https://doi.org/10.1007/978-3-030-48791-1_16

Engineering drawings are common across different domains such as Oil & Gas, construction, mechanical and other domains. Automatic processing and analysis of these drawings is a challenging task. This is partly due to the complexity of these documents... Read More about Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks..

Reducing human effort in engineering drawing validation. (2020)
Journal Article
RICA, E., MORENO-GARCÍA, C.F., ÁLVAREZ, S. and SERRATOS, F. 2020. Reducing human effort in engineering drawing validation. Computers in industry [online], 117, article ID 103198. Available from: https://doi.org/10.1016/j.compind.2020.103198

Oil & Gas facilities are extremely huge and have complex industrial structures that are documented using thousands of printed sheets. During the last years, it has been a tendency to migrate these paper sheets towards a digital environment, with the... Read More about Reducing human effort in engineering drawing validation..

A comparison of feature extractors for panorama stitching in an autonomous car architecture. (2019)
Presentation / Conference Contribution
CORTÉS-GALLARDO, E., MORENO-GARCIA, C.F., ZHU, A., CHÍPULI-SILVA, D., GONZÁLEZ-GONZÁLEZ, J.A., MORALES-ORTIZ, D., FERNÁNDEZ, S., URRIZA, B., VALVERDE-LÓPEZ, J., MARÍN, A., PÉREZ, H., IZQUIERDO-REYES, J. and BUSTAMANTE-BELLO, R. 2019. A comparison of feature extractors for panorama stitching in an autonomous care architecture. In Proceedings of 2019 International conference on mechatronics, electronics and automotive engineering (ICMEAE 2019), 26-29 November 2019, Cuernavaca, Mexico. Piscataway: IEEE [online], page 50-55. Available from: https://doi.org/10.1109/ICMEAE.2019.00017

Panorama stitching consists on frames being put together to create a 360o view. This technique is proposed for its implementation in autonomous vehicles instead of the use of an external 360o camera, mostly due to its reduced cost and improved aerody... Read More about A comparison of feature extractors for panorama stitching in an autonomous car architecture..

Digitisation of assets from the oil and gas industry: challenges and opportunities. (2019)
Presentation / Conference Contribution
MORENO-GARCIA, C.F. and ELYAN, E. 2019. Digitisation of assets from the oil and gas industry: challenges and opportunities. In Proceedings of 2019 International conference on document analysis and recognition workshops (ICDARW), 22-25 September 2019, Sydney, Australia. Piscataway: IEEE [online], 7, pages 2-5. Available from: https://doi.org/10.1109/ICDARW.2019.60122

Automated processing and analysis of legacies of printed documents across the Oil & Gas industry provide a unique opportunity and at the same time pose a significant challenge. One particular example is the case of Piping and Instrumentation Diagrams... Read More about Digitisation of assets from the oil and gas industry: challenges and opportunities..

Generalised median of graph correspondences. (2019)
Journal Article
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2019. Generalised median of graph correspondences. Pattern recognition letters [online], 125, pages 389-395. Available from: https://doi.org/10.1016/j.patrec.2019.05.015

A graph correspondence is defined as a function that maps the elements of two attributed graphs. Due to the increasing availability of methods to perform graph matching, numerous graph correspondences can be deducted for a pair of attributed graphs.... Read More about Generalised median of graph correspondences..

Correspondence edit distance to obtain a set of weighted means of graph correspondences. (2018)
Journal Article
MORENO-GARCÍA, C.F., SERRATOSA, F. and XIAOYI, J. 2020. Correspondence edit distance to obtain a set of weighted means of graph correspondences. Pattern recognition letters [online], 134, pages 29-36. Available from: https://doi.org/10.1016/j.patrec.2018.08.027

Given a pair of data structures, such as strings, trees, graphs or sets of points, several correspondences (also referred in literature as labellings, matchings or assignments) can be defined between their local parts. The Hamming distance has been l... Read More about Correspondence edit distance to obtain a set of weighted means of graph correspondences..

Modelling the generalised median correspondence through an edit distance. (2018)
Presentation / Conference Contribution
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2018. Modelling the generalised median correspondence through an edit distance. In Bai, X., Hancock, E.R., Ho, T.K., Wilson, R.C., Biggio, B. and Robles-Kelly, A. (eds.) Structural, syntactic, and statistical pattern recognition: proceedings of the 2018 Joint International Association for Pattern Recognition (IAPR) international workshops on structural and syntactic pattern recognition (SSPR 2018), and statistical techniques in pattern recognition (SPR 2018) (S+SSPR 2018), 17-19 August 2018, Beijing, China. Lecture notes in computer science, 11004. Cham: Springer [online], pages 271-281. Available from: https://doi.org/10.1007/978-3-319-97785-0_26

On the one hand, classification applications modelled by structural pattern recognition, in which elements are represented as strings, trees or graphs, have been used for the last thirty years. In these models, structural distances are modelled as th... Read More about Modelling the generalised median correspondence through an edit distance..

Symbols classification in engineering drawings. (2018)
Presentation / Conference Contribution
ELYAN, E., MORENO GARCIA, C. and JAYNE, C. 2018. Symbols classification in engineering drawings. In Proceedings of the 2018 International joint conference on neural networks (IJCNN 2018), 8-13 July 2018, Rio de Janeiro, Brazil. Piscataway, NJ: IEEE [online], article number 8489087. Available from: https://doi.org/10.1109/IJCNN.2018.8489087

Technical drawings are commonly used across different industries such as Oil and Gas, construction, mechanical and other types of engineering. In recent years, the digitization of these drawings is becoming increasingly important. In this paper, we p... Read More about Symbols classification in engineering drawings..

Digital interpretation of sensor-equipment diagrams. (2018)
Presentation / Conference Contribution
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..

New trends on digitisation of complex engineering drawings. (2018)
Presentation / Conference Contribution
MORENO-GARCIA, C.F., ELYAN, E. and JAYNE, C. 2019. New trends on digitisation of complex engineering drawings. Neural computing and applications [online], 31(6): selected papers from the proceedings of the 18th Engineering applications of neural networks conference (EANN 2017), 25-27 August 2017, Athens, Greece, pages 1695-1712. Available from: https://doi.org/10.1007/s00521-018-3583-1

Engineering drawings are commonly used across different industries such as oil and gas, mechanical engineering and others. Digitising these drawings is becoming increasingly important. This is mainly due to the legacy of drawings and documents that m... Read More about New trends on digitisation of complex engineering drawings..

Heuristics-based detection to improve text/graphics segmentation in complex engineering drawings. (2017)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..