All Outputs (61)

Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. [Dataset] (2022)
Dataset
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PIRAS, L. and PETROVSKI, A. 2023. Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models [Dataset]. Hosted on GitHub (online). Available from: https://github.com/softwaresec-labs/LVDAndro

Many of the Android apps get published without appropriate security considerations, possibly due to not verifying code or not identifying vulnerabilities at the early stages of development. This can be overcome by using an AI based model trained on a... Read More about Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. [Dataset].

DRL-RNP: deep reinforcement learning-based optimized RNP flight procedure execution. (2022)
Journal Article
ZHU, L., WANG, J., WANG, Y., JI, Y. and REN, J. 2022. DRL-RNP: deep reinforcement learning-based optimized RNP flight procedure execution. Sensors [online], 22(17), article 6475. Available from: https://doi.org/10.3390/s22176475

The required navigation performance (RNP) procedure is one of the two basic navigation specifications for the performance-based navigation (PBN) procedure as proposed by the International Civil Aviation Organization (ICAO) through an integration of t... Read More about DRL-RNP: deep reinforcement learning-based optimized RNP flight procedure execution..

An approach to emotion recognition using brain rhythm sequencing and asymmetric features. (2022)
Journal Article
LI, J.W., CHEN, R.J., BARMA, S., CHEN, F., PUN, S.H., MAK, P.U., WANG, L.J., ZENG, X.X., REN, J.C. and ZHAO, H.M. 2022. An approach to emotion recognition using brain rhythm sequencing and asymmetric features. Cognitive computation [online], 14(6), pages 2260-2273. Available from: https://doi.org/10.1007/s12559-022-10053-z

Emotion can be influenced during self-isolation, and to avoid severe mood swings, emotional regulation is meaningful. To achieve this, efficiently recognizing emotion is a vital step, which can be realized by electroencephalography signals. Previousl... Read More about An approach to emotion recognition using brain rhythm sequencing and asymmetric features..

Analysing the fitness landscape rotation for combinatorial optimisation. (2022)
Conference Proceeding
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2022. Analysing the fitness landscape rotation for combinatorial optimisation. In Rudolph, G., Kononova, A.V., Aguirre, H., Kerschke, P., Ochoa, G. and Tušar, T. (eds.) Parallel problem solving from nature (PPSN XVII): proceedings of 17th Parallel problem solving from nature international conference 2022 (PPSN 2022), 10-14 September 2022, Dortmund, Germany. Lecture notes in computer science, 13398. Cham: Springer [online], pages 533-547. Available from: https://doi.org/10.1007/978-3-031-14714-2_37

Fitness landscape rotation has been widely used in the field of dynamic combinatorial optimisation to generate test problems with academic purposes. This method changes the mapping between solutions and objective values, but preserves the structure o... Read More about Analysing the fitness landscape rotation for combinatorial optimisation..

ICOSeg: real-time ICOS protein expression segmentation from immunohistochemistry slides using a lightweight conv-transformer network. (2022)
Journal Article
SINGH, V.K., SARKER, M.M.K., MAKHLOUF, Y., CRAIG, S.G., HUMPHRIES, M.P., LOUGHREY, M.B., JAMES, J.A., SALTO-TELLEZ, M., O'REILLY, P. and MAXWELL, P. 2022. ICOSeg: real-time ICOS protein expression segmentation from immunohistochemistry slides using a lightweight conv-transformer network. Cancers [online], 14(16), article 3910. Available from: https://doi.org/10.3390/cancers14163910

In this article, we propose ICOSeg, a lightweight deep learning model that accurately segments the immune-checkpoint biomarker, Inducible T-cell COStimulator (ICOS) protein in colon cancer from immunohistochemistry (IHC) slide patches. The proposed m... Read More about ICOSeg: real-time ICOS protein expression segmentation from immunohistochemistry slides using a lightweight conv-transformer network..

TransSLC: skin lesion classification in dermatoscopic images using transformers. (2022)
Conference Proceeding
SARKER, M.M.K., MORENO-GARCÍA, C.F., REN, J. and ELYAN, E. 2022. TransSLC: skin lesion classification in dermatoscopic images using transformers. In Yang, G., Aviles-Rivero, A., Roberts, M. and Schönlieb, C.-B. (eds.) Medical image understanding and analysis: proceedings of 26th Medical image understanding and analysis 2022 (MIUA 2022), 27-29 July 2022, Cambridge, UK. Lecture notes in computer sciences, 13413. Cham: Springer [online], pages 651-660. Available from: https://doi.org/10.1007/978-3-031-12053-4_48

Early diagnosis and treatment of skin cancer can reduce patients' fatality rates significantly. In the area of computer-aided diagnosis (CAD), the Convolutional Neural Network (CNN) has been widely used for image classification, segmentation, and rec... Read More about TransSLC: skin lesion classification in dermatoscopic images using transformers..

Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. (2022)
Conference Proceeding
DANG, T., LUONG, A.V., LIEW, A.W.C., MCCALL, J. and NGUYEN, T.T. 2022. Ensemble of deep learning models with surrogate-based optimization for medical image segmentation. In 2022 IEEE (Institute of Electrical and Electronics Engineers) Congress on evolutionary computation (CEC 2022), co-located with 2022 IEEE International joint conferences on neural networks (IJCNN 2022), 2022 IEEE International conference on fuzzy systems (FUZZ-IEEE 2022), 18-23 July 2022, Padua, Italy. Piscataway: IEEE (online), article #1030. Available from: https://doi.org/10.1109/CEC55065.2022.9870389

Deep Neural Networks (DNNs) have created a breakthrough in medical image analysis in recent years. Because clinical applications of automated medical analysis are required to be reliable, robust and accurate, it is necessary to devise effective DNNs... Read More about Ensemble of deep learning models with surrogate-based optimization for medical image segmentation..

Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. (2022)
Conference Proceeding
OGUNSEMI, A., MCCALL, J., KERN, M., LACROIX, B., CORSAR, D. and OWUSU, G. 2022. Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem. In Fieldsend, J. (ed.) GECCO'22 companion: proceedings of 2022 Genetic and evolutionary computation conference companion, 9-13 July 2022, Boston, USA, [virtual event]. New York: ACM [online], pages 735-738. Available from: https://doi.org/10.1145/3520304.3529033

There is a growing literature spanning several research communities that studies multiple optimisation problems whose solutions interact, thereby leading researchers to consider suitable approaches to joint solution. Real-world problems, like supply... Read More about Facility location problem and permutation flow shop scheduling problem: a linked optimisation problem..

Nondestructive detection and grading of flesh translucency in pineapples with visible and near-infrared spectroscopy. (2022)
Journal Article
XU, S., REN, J., LU, H., WANG, X., SUN, X. and LIANG, X. 2022. Nondestructive detection and grading of flesh translucency in pineapples with visible and near-infrared spectroscopy. Postharvest biology and technology [online], 192, article 112029. Available from: https://doi.org/10.1016/j.postharvbio.2022.112029

Rapid, accurate, and nondestructive internal quality detection for large and rough surface fruit, such as translucency in pineapples, is challenging. In this paper, a visible and near infrared (VIS/NIR) spectrum-based platform is proposed for optimiz... Read More about Nondestructive detection and grading of flesh translucency in pineapples with visible and near-infrared spectroscopy..

An artificial neural network algorithm to retrieve chlorophyll a for Northwest European shelf seas from top of atmosphere ocean colour reflectance. (2022)
Journal Article
HADJAL, M., MEDINA-LOPEZ, E., REN, J., GALLEGO, A. and MCKEE, D. 2022. An artificial neural network algorithm to retrieve chlorophyll a for Northwest European shelf seas from top of atmosphere ocean colour reflectance. Remote sensing [online], 14(14), article 3353. Available from: https://doi.org/10.3390/rs14143353

Chlorophyll-a (Chl) retrieval from ocean colour remote sensing is problematic for relatively turbid coastal waters due to the impact of non-algal materials on atmospheric correction and standard Chl algorithm performance. Artificial neural networks (... Read More about An artificial neural network algorithm to retrieve chlorophyll a for Northwest European shelf seas from top of atmosphere ocean colour reflectance..

A novel band selection and spatial noise reduction method for hyperspectral image classification. (2022)
Journal Article
FU, H., ZHANG, A., SUN, G., REN, J., JIA, X., PAN, Z. and MA, H. 2022. A novel band selection and spatial noise reduction method for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5535713. Available from: https://doi.org/10.1109/TGRS.2022.3189015

As an essential reprocessing method, dimensionality reduction (DR) can reduce the data redundancy and improve the performance of hyperspectral image (HSI) classification. A novel unsupervised DR framework with feature interpretability, which integrat... Read More about A novel band selection and spatial noise reduction method for hyperspectral image classification..

An assessment on effect of process parameters on pull force during pultrusion. (2022)
Journal Article
MUKHERJI, A. and NJUGUNA, J. 2022. An assessment on effect of process parameters on pull force during pultrusion. International journal of advanced manufacturing technology [online], 121(5-6), pages 3419-3439. Available from: https://doi.org/10.1007/s00170-022-09221-0

This research investigates the process behaviour by prediction of the pull force required to drag the raw materials through heated die at different reinforcing material configuration during pultrusion. Pultrusion is a continuous manufacturing process... Read More about An assessment on effect of process parameters on pull force during pultrusion..

The intersection of evolutionary computation and explainable AI. (2022)
Conference Proceeding
BACARDIT, J., BROWNLEE, A.E.I., CAGNONI, S., IACCA, G., MCCALL, J. and WALKER, D. 2022. The intersection of evolutionary computation and explainable AI. In Fieldsend, J. (ed.) GECCO'22 companion: proceedings of 2022 Genetic and evolutionary computation conference companion, 9-13 July 2022, Boston, USA, [virtual event]. New York: ACM [online], pages 1757-1762. Available from: https://doi.org/10.1145/3520304.3533974

In the past decade, Explainable Artificial Intelligence (XAI) has attracted a great interest in the research community, motivated by the need for explanations in critical AI applications. Some recent advances in XAI are based on Evolutionary Computat... Read More about The intersection of evolutionary computation and explainable AI..

A music cognition-guided framework for multi-pitch estimation. (2022)
Journal Article
LI, X., YAN, Y., SORAGHAN, J., WANG, Z. and REN, J. 2023. A music cognition-guided framework for multi-pitch estimation. Cognitive computation [online], 15(1), pages 23-35. Available from: https://doi.org/10.1007/s12559-022-10031-5

As one of the most important subtasks of automatic music transcription (AMT), multi-pitch estimation (MPE) has been studied extensively for predicting the fundamental frequencies in the frames of audio recordings during the past decade. However, how... Read More about A music cognition-guided framework for multi-pitch estimation..

Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM). (2022)
Journal Article
ROHAN, A. 2022 Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM). Mathematics [online], 10(12), article number 2031. Available from: https://doi.org/10.3390/math10122031

In the current Industry 4.0 revolution, prognostics and health management (PHM) is an emerging field of research. The difficulty of obtaining data from electromechanical systems in an industrial setting increases proportionally with the scale and acc... Read More about Holistic fault detection and diagnosis system in imbalanced, scarce, multi-domain (ISMD) data setting for component-level prognostics and health management (PHM)..

Sparse data-extended fusion method for sea surface temperature prediction on the East China Sea. (2022)
Journal Article
WANG, X., WANG, L., ZHANG, Z., CHEN, K., JIN, Y., YAN, Y. and LIU, J. 2022. Sparse data-extended fusion method for sea surface temperature prediction on the East China Sea. Applied sciences [online], 12(12); intelligent computing and remote sensing, article 5905. Available from: https://doi.org/10.3390/app12125905

The accurate temperature background field plays a vital role in the numerical prediction of sea surface temperature (SST). At present, the SST background field is mainly derived from multi-source data fusion, including satellite SST data and in situ... Read More about Sparse data-extended fusion method for sea surface temperature prediction on the East China Sea..

Multi-criteria material selection for casing pipe in shale gas wells application. (2022)
Journal Article
MOHAMMED, A.I., BARTLETT, M., OYENEYIN, B., KAYVANTASH, K. and NJUGUNA, J. 2022. Multi-criteria material selection for casing pipe in shale gas wells application. Journal of petroleum exploration and production technology [online], 12(12), pages 3183-3199. Available from: https://doi.org/10.1007/s13202-022-01506-0

The conventional method of casing selection is based on availability and/or order placement to manufacturers based on certain design specifications to meet the anticipated downhole conditions. This traditional approach is very much dependent on exper... Read More about Multi-criteria material selection for casing pipe in shale gas wells application..

IR-capsule: two-stream network for face forgery detection. (2022)
Journal Article
LIN, K., HAN, W., LI, S., GU, Z., ZHAO, H., REN, J., ZHU, L. and LV, J. 2023 IR-capsule: two-stream network for face forgery detection. Cognitive computation [online], 15(1), pages 13-22. Available from: https://doi.org/10.1007/s12559-022-10008-4

With the emergence of deep learning, generating forged images or videos has become much easier in recent years. Face forgery detection, as a way to detect forgery, is an important topic in digital media forensics. Despite previous works having made r... Read More about IR-capsule: two-stream network for face forgery detection..

SC2Net: a novel segmentation-based classification network for detection of COVID-19 in chest X-ray images. (2022)
Journal Article
ZHAO, H., FANG, Z., REN, J., MACLELLAN, C., XIA, Y., SUN, M. and REN, K. 2022. SC2Net: a novel segmentation-based classification network for detection of COVID-19 in chest X-ray images. IEEE journal of biomedical and health informatics [online], 26(8), pages 4032-4043. Available from: https://doi.org/10.1109/JBHI.2022.3177854

The pandemic of COVID-19 has become a global crisis in public health, which has led to a massive number of deaths and severe economic degradation. To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial. As the popularly u... Read More about SC2Net: a novel segmentation-based classification network for detection of COVID-19 in chest X-ray images..

Multi-scale spatial fusion and regularization induced unsupervised auxiliary task CNN model for deep super-resolution of hyperspectral image. (2022)
Journal Article
HA, V.K., REN, J., WANG, Z., SUN, G., ZHAO, H. and MARSHALL, S. 2022. Multi-scale spatial fusion and regularization induced unsupervised auxiliary task CNN model for deep super-resolution of hyperspectral image. IEEE journal of selected topics in applied earth observations and remote sensing [online], 15, pages 4583-4598. Available from: https://doi.org/10.1109/JSTARS.2022.3176969

Hyperspectral images (HSI) features rich spectral information in many narrow bands but at a cost of a relatively low spatial resolution. As such, various methods have been developed for enhancing the spatial resolution of the low-resolution HSI (Lr-H... Read More about Multi-scale spatial fusion and regularization induced unsupervised auxiliary task CNN model for deep super-resolution of hyperspectral image..