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All Outputs (9)

Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers. (2024)
Journal Article
HAYNES, S.C., JOHNSTON, P. and ELYAN, E. 2024. Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers. Multimedia tools and applications [online], Latest Articles. Available from: https://doi.org/10.1007/s11042-024-18543-y

The generalisability of deep neural network classifiers is emerging as one of the most important challenges of our time. The recent COVID-19 pandemic led to a surge of deep learning publications that proposed novel models for the detection of COVID-1... Read More about Generalisation challenges in deep learning models for medical imagery: insights from external validation of COVID-19 classifiers..

Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance. (2023)
Journal Article
FORBES-MCKAY, K.E., BREMNER, P.A.M., JOHNSTON, P. and AIR, C. [2024]. Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance. Journal of applied research in higher education [online], EarlyCite. Available from: https://doi.org/10.1108/jarhe-06-2023-0253

This study addresses gaps in the existing literature on students' understanding of Independent Learning (IL), whilst exploring the link between levels of IL, growth mindset, motivated strategies for learning and academic performance. Three hundred an... Read More about Exploring independent learning (IL) and its relationship to mindset, motivated strategies for learning and academic performance..

Fusion methods for face presentation attack detection. (2022)
Journal Article
ABDULLAKUTTY, F., JOHNSTON, P. and ELYAN, E. 2022. Fusion methods for face presentation attack detection. Sensors [online], 22(14): soft sensors 2021-2022, article 5196. Available from: https://doi.org/10.3390/s22145196

Face presentation attacks (PA) are a serious threat to face recognition (FR) applications. These attacks are easy to execute and difficult to detect. An attack can be carried out simply by presenting a video, photo, or mask to the camera. The literat... Read More about Fusion methods for face presentation attack detection..

Deep transfer learning on the aggregated dataset for face presentation attack detection. (2022)
Journal Article
ABDULLAKUTTY, F., ELYAN, E., JOHNSTON, P. and ALI-GOMBE, A. 2022. Deep transfer learning on the aggregated dataset for face presentation attack detection. Cognitive computation [online], 14(6), pages 2223-2233. Available from: https://doi.org/10.1007/s12559-022-10037-z

Presentation attacks are becoming a serious threat to one of the most common biometric applications, namely face recognition (FR). In recent years, numerous methods have been presented to detect and identify these attacks using publicly available dat... Read More about Deep transfer learning on the aggregated dataset for face presentation attack detection..

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..

A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods. (2021)
Journal Article
ABDULLAKUTTY, F., ELYAN, E. and JOHNSTON, P. 2021. A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods. Information fusion [online], 75, pages 55-69. Available from: https://doi.org/10.1016/j.inffus.2021.04.015

Face Recognition is considered one of the most common biometric solutions these days and is widely used across a range of devices for various security purposes. The performance of FR systems has improved by orders of magnitude over the past decade. T... Read More about A review of state-of-the-art in face presentation attack detection: from early development to advanced deep learning and multi-modal fusion methods..

Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. (2021)
Journal Article
CARLOTO, I., JOHNSTON, P., PESTANA, C.J. and LAWTON, L.A. 2021. Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks. Science of the total environment [online], 784, article 146956. Available from: https://doi.org/10.1016/j.scitotenv.2021.146956

The presence of harmful algal bloom in many reservoirs around the world, alongside the lack of sanitation law/ordinance regarding cyanotoxin monitoring (particularly in developing countries), create a scenario in which the local population could pote... Read More about Detection of morphological changes caused by chemical stress in the cyanobacterium Planktothrix agardhii using convolutional neural networks..

Video tampering localisation using features learned from authentic content. (2019)
Journal Article
JOHNSTON, P., ELYAN, E. and JAYNE, C. 2020. Video tampering localisation using features learned from authentic content. Neural computing and applications [online], 32(16): special issue on Real-world optimization problems and meta-heuristics and selected papers from the 19th Engineering applications of neural networks conference 2018 (EANN 2018), 3-5 September 2018, Bristol UK , pages 12243-12257. Available from: https://doi.org/10.1007/s00521-019-04272-z

Video tampering detection remains an open problem in the field of digital media forensics. As video manipulation techniques advance, it becomes easier for tamperers to create convincing forgeries that can fool human eyes. Deep learning methods have a... Read More about Video tampering localisation using features learned from authentic content..

A review of digital video tampering: from simple editing to full synthesis. (2019)
Journal Article
JOHNSTON, P. and ELYAN, E. 2019. A review of digital video tampering: from simple editing to full synthesis. Digital investigation [online], 29, pages 67-81. Available from: https://doi.org/10.1016/j.diin.2019.03.006

Video tampering methods have witnessed considerable progress in recent years. This is partly due to the rapid development of advanced deep learning methods, and also due to the large volume of video footage that is now in the public domain. Historica... Read More about A review of digital video tampering: from simple editing to full synthesis..