Outputs (121)

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..

Automation and cyber security risks on the railways: the human factors implications. (2022)
Presentation / Conference
THON, E. and FAILY, S. 2022. Automation and cyber security risks on the railways: the human factors implications. Presented at the 2022 International conference on ergonomics and human factors, part one (EHF2022 Online), 11-12 April 2022, [virtual event].

Automation improves rail passenger experience, but may reduce cyber resilience because it fails to adequately account for human factors. Preliminary results from a study on signallers and automation confirms this, but judicious use of modelling tools... Read More about Automation and cyber security risks on the railways: the human factors implications..

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..

Detection of image forgery for forensic analytics. (2022)
Conference Proceeding
SRI, C.G., BANO, S., TRINADH, V.B., VALLURI, V.V. and THUMATI, H. 2022. Detection of image forgery for forensic analytics. In Aurelia, S., Hiremath, S.S., Subramanian, K. and Biswas, S.K. (eds.) Select proceedings of the 2021 International conference on sustainable advanced computing (ICSAC 2021), 5-6 March 2021, Bangalore, India. Lecture notes in electrical engineering, 840. Singapore: Springer [online], pages 321-338. Available from: https://doi.org/10.1007/978-981-16-9012-9_26

Due to the technical revolution in digital image processing, different advanced image manipulation software has been used in recent years to produce new unrealistic images without leaving evidence of what is happening in the world, so it would be dif... Read More about Detection of image forgery for forensic analytics..

Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. (2022)
Conference Proceeding
YAN, Y., ZHANG, Y., REN, J., HADJAL, M., MCKEE, D., KAO, F.-J., and DURRANI, T. 2022. Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 582-587. Available from: https://doi.org/10.1007/978-981-19-0390-8_71

Marine Scotland is tasked with reporting on the environmental status of Scottish marine waters, an enormous area of water extending from the shoreline to deep oceanic waters. As one of the most important variables, chlorophyll concentration (Chl) pla... Read More about Estimation of chlorophyll concentration for environment monitoring in Scottish marine water..

Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation. (2022)
Conference Proceeding
CHEN, S., YAN, Y., REN, J., HWANG, B., MARSHALL, S. and DARRANI, T. 2022. Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 1004-1012. Available from: https://doi.org/10.1007/978-981-19-0390-8_126

By grouping pixels with visual coherence, superpixel algorithms provide an alternative representation of regular pixel grid for precise and efficient image segmentation. In this paper, a multi-stage model is used for sea ice segmentation from the hig... Read More about Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation..

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..