All Outputs (393)

Cultural factors related to childhood and adolescent obesity in Mexico: a systematic review of qualitative studies. (2022)
Journal Article
ACEVES-MARTINS, M., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GODINA-FLORES, N.L., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Cultural factors related to childhood and adolescent obesity in Mexico: a systematic review of qualitative studies. Obesity reviews [online], 23(9), article e13461. Available from: https://doi.org/10.1111/obr.13461

Culture and culturally specific beliefs or practices may influence perceptions and decisions, potentially contributing to childhood obesity. The objective of this study is to identify the cultural factors (expressed through decisions, behaviors, indi... Read More about Cultural factors related to childhood and adolescent obesity in Mexico: a systematic review of qualitative studies..

Novel hyperbolic clustering-based band hierarchy (HCBH) for effective unsupervised band selection of hyperspectral images. (2022)
Journal Article
SUN, H., ZHANG, L., REN, J. and HUANG, H. 2022. Novel hyperbolic clustering-based band hierarchy (HCBH) for effective unsupervised band selection of hyperspectral images. Pattern recognition [online], 130, article number 108788. Available from: https://doi.org/10.1016/j.patcog.2022.108788

For dimensionality reduction of HSI, many clustering-based unsupervised band selection (UBS) methods have been proposed due to their superiority of reducing the high redundancy between selected bands. However, most of these methods fail to reflect th... Read More about Novel hyperbolic clustering-based band hierarchy (HCBH) for effective unsupervised band selection of hyperspectral images..

Demystifying the black box: the importance of interpretability of predictive models in neurocritical care. (2022)
Journal Article
MOSS, L., CORSAR, D., SHAW, M., PIPER, I. and HAWTHORNE, C. 2022. Demystifying the black box: the importance of interpretability of predictive models in neurocritical care. Neurocritical care [online], 37(Supplement 2): big data in neurocritical care, pages 185-191. Available from: https://doi.org/10.1007/s12028-022-01504-4

Neurocritical care patients are a complex patient population, and to aid clinical decision-making, many models and scoring systems have previously been developed. More recently, techniques from the field of machine learning have been applied to neuro... Read More about Demystifying the black box: the importance of interpretability of predictive models in neurocritical care..

Obesity and oral health in Mexican children and adolescents: systematic review and meta-analysis. (2022)
Journal Article
ACEVES-MARTINS, M., GODINA-FLORES, N.L., GUTIERREZ-GÓMEZ, Y.Y., RICHARDS, D., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M. and MORENO-GARCÍA, C.F. 2021. Obesity and oral health in Mexican children and adolescents: systematic review and meta-analysis. Nutrition reviews [online], 80(6), pages 1694-1710. Available from: https://doi.org/10.1093/nutrit/nuab088

Context: A relationship between obesity and poor oral health has been reported. Objective: To investigate the association between overweight/obesity and oral health in Mexican children and adolescents. Data Sources: A literature search was conducted... Read More about Obesity and oral health in Mexican children and adolescents: systematic review and meta-analysis..

Multi-sourced sensing and support vector machine classification for effective detection of fire hazard in early stage. (2022)
Journal Article
CHEN, S., REN, J., YAN, Y., SUN, M., HU, F. and ZHAO, H. 2022. Multi-sourced sensing and support vector machine classification for effective detection of fire hazard in early stage. Computers and electrical engineering [online], 101, article 108046. Available from: https://doi.org/10.1016/j.compeleceng.2022.108046

Accurate detection and early warning of fire hazard are crucial for reducing the associated damages. Due to the limitations of smoke-based detection mechanism, most commercial detectors fail to distinguish the smoke from dust and steam, leading to fr... Read More about Multi-sourced sensing and support vector machine classification for effective detection of fire hazard in early stage..

Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification. (2022)
Journal Article
ZHANG, A., PAN, Z., FU, H., SUN, G., RONG, J., REN, J., JIA, X. and YAO, Y. 2022. Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification. Remote sensing [online], 14(9), article 2125. Available from: https://doi.org/10.3390/rs14092125

Joint sparse representation classification (JSRC) is a representative spectral–spatial classifier for hyperspectral images (HSIs). However, the JSRC is inappropriate for highly heterogeneous areas due to the spatial information being extracted from a... Read More about Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification..

A DRL-based service offloading approach using DAG for edge computational orchestration. (2022)
Journal Article
MEKALA, M.S., DHIMAN, G., SRIVASTAV, G., NAIN, Z., ZHANG, H., VIRIYASITAVAT, W. and VARMA, G.P.S. 2022. A DRL-based service offloading approach using DAG for edge computational orchestration. IEEE transactions on computational social systems [online], Early Access. Available from: https://doi.org/10.1109/tcss.2022.3161627

Edge infrastructure and Industry 4.0 required services are offered by edge-servers (ESs) with different computation capabilities to run social application's workload based on a leased-price method. The usage of Social Internet of Things (SIoT) applic... Read More about A DRL-based service offloading approach using DAG for edge computational orchestration..

Implementation of NAO robot maze navigation based on computer vision and collaborative learning. (2022)
Journal Article
MAGALLÁN-RAMÍREZ, D., MARTÍNEZ-AGUILAR, J.D., RODRÍGUEZ-TIRADO, A., BALDERAS, D., LÓPEZ-CAUDANA, E.O. AND MORENO-GARCÍA, C.F. 2022. Implementation of NAO robot maze navigation based on computer vision and collaborative learning. Frontiers in robotics and AI [online], 9, article 834021. Available from: https://doi.org/10.3389/frobt.2022.834021

Maze navigation using one or more robots has become a recurring challenge in scientific literature and real life practice, with fleets having to find faster and better ways to navigate environments such as a travel hub, airports, or for evacuation of... Read More about Implementation of NAO robot maze navigation based on computer vision and collaborative learning..

Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. (2022)
Journal Article
ELYAN, E., VUTTIPITTAYAMONGKOL, P., JOHNSTON, P., MARTIN, K., MCPHERSON, K., MORENO-GARCIA, C.F., JAYNE, C. and SARKER, M.M.K. 2022. Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward. Artificial intelligence surgery [online], 2, pages 24-25. Available from: https://doi.org/10.20517/ais.2021.15

The recent development in the areas of deep learning and deep convolutional neural networks has significantly progressed and advanced the field of computer vision (CV) and image analysis and understanding. Complex tasks such as classifying and segmen... Read More about Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward..

Assessing system of systems information security risk with OASoSIS. (2022)
Journal Article
KI-ARIES, D., FAILY, S., DOGAN, H. and WILLIAMS, C. 2022. Assessing system of systems information security risk with OASoSIS. Computers and security [online], 117, article 102690. Available from: https://doi.org/10.1016/j.cose.2022.102690

The term System of Systems (SoS) is used to describe the coming together of independent systems, collaborating to achieve a new or higher purpose. However, the SoS concept is often misunderstood within operational environments, providing challenges t... Read More about Assessing system of systems information security risk with OASoSIS..

Antimicrobial resistance and machine learning: challenges and opportunities. (2022)
Journal Article
ELYAN, E., HUSSAIN, A., SHEIKH, A., ELMANAMA, A.A., VUTTPITTAYAMONGKOL, P. and HIJAZI, K. 2022. Antimicrobial resistance and machine learning: challenges and opportunities. IEEE access [online], 10, pages 31561-31577. Available from: https://doi.org/10.1109/ACCESS.2022.3160213

Antimicrobial Resistance (AMR) has been identified by the World Health Organisation (WHO) as one of the top ten global health threats. Inappropriate use of antibiotics around the world and in particular in Low-to-Middle-Income Countries (LMICs), wher... Read More about Antimicrobial resistance and machine learning: challenges and opportunities..

MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. (2022)
Journal Article
LI, M., WANG, Z., REN, J. and SUN, M. 2022. MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi‑type feature–based strong generalization. Cognitive computation [online], 14(4), pages 1435-1445. Available from: https://doi.org/10.1007/s12559-021-09947-1

With the increasing popularity of short videos on various social media platforms, there is a great challenge for evaluating the aesthetic quality of these videos. In this paper, we first construct a large-scale and properly annotated short video aest... Read More about MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization..

Non-destructive testing of composite fibre materials with hyperspectral imaging: evaluative studies in the EU H2020 FibreEUse project. (2022)
Journal Article
YAN, Y., REN, J., ZHAO, H., WINDMILL, J.F.C., IJOMAH, W., DE WIT, J. and VON FREEDEN, J. 2022. Non-destructive testing of composite fibre materials with hyperspectral imaging: evaluative studies in the EU H2020 FibreEUse project. IEEE transactions on instrumentation and measurement [online], 71, article 6002213. Available from: https://doi.org/10.1109/TIM.2022.3155745

Through capturing spectral data from a wide frequency range along with the spatial information, hyperspectral imaging (HSI) can detect minor differences in terms of temperature, moisture and chemical composition. Therefore, HSI has been successfully... Read More about Non-destructive testing of composite fibre materials with hyperspectral imaging: evaluative studies in the EU H2020 FibreEUse project..

Using artificial intelligence methods for systematic review in health sciences: a systematic review. (2022)
Journal Article
BLAIZOT, A., VEETTIL, S.K., SAIDOUNG, P., MORENO-GARCIA, C.F., WIRATUNGA, N., ACEVES-MARTINS, M., LAI, N.M. and CHAIYAKUNAPRUK, N. 2022. Using artificial intelligence methods for systematic review in health sciences: a systematic review. Research synthesis methods [online], 13(3), pages 353-362. Available from: https://doi.org/10.1002/jrsm.1553

The exponential increase in published articles makes a thorough and expedient review of literature increasingly challenging. This review delineated automated tools and platforms that employ artificial intelligence (AI) approaches and evaluated the re... Read More about Using artificial intelligence methods for systematic review in health sciences: a systematic review..

PS-net: progressive selection network for salient object detection. (2022)
Journal Article
REN, J., WANG, Z. and REN, J. 2022. PS-net: progressive selection network for salient object detection. Cognitive computation [online], 14(2), pages 794-804. Available from: https://doi.org/10.1007/s12559-021-09952-4

Low-level features contain abundant details and high-level features have rich semantic information. Integrating multi-scale features in an appropriate way is significant for salient object detection. However, direct concatenation or addition taken by... Read More about PS-net: progressive selection network for salient object detection..

Psychosocial impact of 8 weeks COVID-19 quarantine on Italian parents and their children. (2022)
Journal Article
KHOORY, B.J., KEUNING, M.W., FLEDDERUS, A.C., CICCHELLI, R., FANOS, V., KHOORY, J., NERVI, D., ELYAN, E., VUTTIPITTAYAMONGKOL, P., OOMEN, M.W.N., PAJKRT, P. and ABU HILAL, M. 2022. Psychosocial impact of 8 weeks COVID-19 quarantine on Italian parents and their children. Maternal and child health journal [online], 26(6), pages 1312-1321. Available from: https://doi.org/10.1007/s10995-021-03311-3

Objectives: Italy was affected greatly by Coronavirus disease 2019 (COVID-19), emerging mainly in the Italian province of Lombardy. This outbreak led to profound governmental interventions along with a strict quarantine. This quarantine may have psyc... Read More about Psychosocial impact of 8 weeks COVID-19 quarantine on Italian parents and their children..

SAM-Net: semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications. (2021)
Journal Article
YANG, B., XU, X., REN, J., CHENG, L. GUO, L. and ZHANG, Z. 2022. SAM-Net: semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications. Pattern recognition letters [online], 153, pages 126-135. Available from: https://doi.org/10.1016/j.patrec.2021.11.028

3D scene understanding is an essential research topic in the field of Visual Odometry (VO). VO is usually built under the assumption of a static environment, which does not always hold in real scenarios. Existing works fail to consider the dynamic ob... Read More about SAM-Net: semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications..

Interventions to prevent obesity in Mexican children and adolescents: systematic review. (2021)
Journal Article
ACEVES-MARTINS, M., LÓPEZ-CRUZ, L., GARCÍA-BOTELLO, M., GUTIERREZ-GÓMEZ, Y.Y. and MORENO-GARCÍA, C.F. 2022. Interventions to prevent obesity in Mexican children and adolescents: systematic review. Prevention science [online], 23(4), pages 563-586. Available from: https://doi.org/10.1007/s11121-021-01316-6

The prevalence of overweight and obesity has been rising among Mexican children and adolescents in the last decades. To systematically review obesity prevention interventions delivered to Mexican children and adolescents. Thirteen databases and one s... Read More about Interventions to prevent obesity in Mexican children and adolescents: systematic review..

FedSim: similarity guided model aggregation for federated learning. (2021)
Journal Article
PALIHAWADANA, C., WIRATUNGA, N., WIJEKOON, A. and KALUTARAGE, H. 2022. FedSim: similarity guided model aggregation for federated learning. Neurocomputing [online], 483: distributed machine learning, optimization and applications, pages 432-445. Available from: https://doi.org/10.1016/j.neucom.2021.08.141

Federated Learning (FL) is a distributed machine learning approach in which clients contribute to learning a global model in a privacy preserved manner. Effective aggregation of client models is essential to create a generalised global model. To what... Read More about FedSim: similarity guided model aggregation for federated learning..

Multi-segment majority voting decision fusion for MI EEG brain-computer interfacing. (2021)
Journal Article
PADFIELD, N., REN, J., QING, C., MURRAY, P., ZHAO, H. and ZHENG, J. 2021. Multi-segment majority voting decision fusion for MI EEG brain-computer interfacing. Cognitive computation [online], 13(6), pages 1484-1495. Available from: https://doi.org/10.1007/s12559-021-09953-3

Brain-computer interfaces (BCIs) based on the electroencephalogram (EEG) generated during motor imagery (MI) have the potential to be used in brain-controlled prosthetics, neurorehabilitation and gaming. Many MI EEG classification systems segment EEG... Read More about Multi-segment majority voting decision fusion for MI EEG brain-computer interfacing..