Outputs (55)

Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. (2021)
Journal Article
ACEVES-MARTINS, A., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(3), pages 544-560. Available from: https://doi.org/10.1093/nutrit/nuab041

Context: Prevalence of overweight and obesity has been rising in the past 3 decades among Mexican children and adolescents. Objective: To systematically review experimental studies evaluating interventions to treat obesity in Mexican children and ado... Read More about Interventions to treat obesity in Mexican children and adolescents: systematic review and meta-analysis..

Class-decomposition and augmentation for imbalanced data sentiment analysis. (2021)
Conference Proceeding
MORENO-GARCIA, C.F., JAYNE, C. and ELYAN, E. 2021. Class-decomposition and augmentation for imbalanced data sentiment analysis. In Proceedings of 2021 International joint conference on neural networks (IJCNN 2021), 18-22 July 2021, [virtual conference]. Piscataway: IEEE [online], article 9533603. Available from: https://doi.org/10.1109/IJCNN52387.2021.9533603

Significant progress has been made in the area of text classification and natural language processing. However, like many other datasets from across different domains, text-based datasets may suffer from class-imbalance. This problem leads to model's... Read More about Class-decomposition and augmentation for imbalanced data sentiment analysis..

Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. (2021)
Conference Proceeding
DANG, T., NGUYEN, T.T., MORENO-GARCIA, C.F., ELYAN, E. and MCCALL, J. 2021. Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation. In Proceeding of 2021 IEEE (Institute of electrical and electronics engineers) Congress on evolutionary computation (CEC 2021), 28 June - 1 July 2021, Kraków, Poland : [virtual conference]. Piscataway: IEEE [online], pages 744-751. Available from: https://doi.org/10.1109/CEC45853.2021.9504929

In recent years, deep learning has rapidly become a method of choice for segmentation of medical images. Deep neural architectures such as UNet and FPN have achieved high performances on many medical datasets. However, medical image analysis algorith... Read More about Weighted ensemble of deep learning models based on comprehensive learning particle swarm optimization for medical image segmentation..

Face detection with YOLO on edge. (2021)
Conference Proceeding
ALI-GOMBE, A., ELYAN, E., MORENO-GARCIA, C.F. and ZWIEGELAAR, J. 2021. Face detection with YOLO on edge. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Enginering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 284-292. Available from: https://doi.org/10.1007/978-3-030-80568-5_24

Significant progress has been achieved in objects detection applications such as Face Detection. This mainly due to the latest development in deep learning-based approaches and especially in the computer vision domain. However, deploying deep-learnin... Read More about Face detection with YOLO on edge..

Image pre-processing and segmentation for real-time subsea corrosion inspection. (2021)
Conference Proceeding
PIRIE, C. and MORENO-GARCIA, C.F. 2021. Image pre-processing and segmentation for real-time subsea corrosion inspection. In Iliadis, L., Macintyre, J., Jayne, C. and Pimenidis, E. (eds.). Proceedings of the 22nd Engineering applications of neural networks conference (EANN2021), 25-27 June 2021, Halkidiki, Greece. Proceedings of the International Neural Networks Society (INNS), 3. Cham: Springer [online], pages 220-231. Available from: https://doi.org/10.1007/978-3-030-80568-5_19

Inspection engineering is a highly important field in the Oil & Gas sector for analysing the health of offshore assets. Corrosion, a naturally occurring phenomenon, arises as a result of a chemical reaction between a metal and its environment, causin... Read More about Image pre-processing and segmentation for real-time subsea corrosion inspection..

Two layer ensemble of deep learning models for medical image segmentation. [Preprint] (2021)
Working Paper
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2021. Two layer ensemble of deep learning models for medical image segmentation. arXiv [online]. Available from: https://doi.org/10.48550/arXiv.2104.04809

In recent years, deep learning has rapidly become a method of choice for the segmentation of medical images. Deep Neural Network (DNN) architectures such as UNet have achieved state-of-the-art results on many medical datasets. To further improve the... Read More about Two layer ensemble of deep learning models for medical image segmentation. [Preprint].

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)
Journal Article
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 conference], 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)
Conference Proceeding
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 conference]. 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)
Conference Proceeding
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..