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The state of the art in hydrogen storage. (2023)
Journal Article
REYNOLDS, J., ALI, D. and NJUGUNA, J. 2023. The state of the art in hydrogen storage. Green energy and environmental technology [online], (accepted).

The global renewable energy mix is set to change even further with the increasing demand for hydrogen. The production levels are dramatically increasing, and it is becoming prevalent that the storage of hydrogen gas is much more complex than natural... Read More about The state of the art in hydrogen storage..

Effective detection of seismic events by non-classical receptive field visual cognitive modelling. (2023)
Journal Article
ZHAO, J., LEI, HAOJIE, LI, YANG, REN, J., SUN, G., ZHAO, H., SHEN, H. and WANG, D. 2023. Effective detection of seismic events by non-classical receptive field visual cognitive modelling. Journal of seismic exploration [online], 32(4), pages 385-406. Available from: http://www.geophysical-press.com/online/Vol32-4_art6.pdf

The detection and up-picking of the seismic events are critical for seismic data analysis and interpretation. Events picking can be used for sequence stratigraphic analysis, reservoir feature extraction, the determining of the subsequent reflection i... Read More about Effective detection of seismic events by non-classical receptive field visual cognitive modelling..

Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system. (2023)
Journal Article
RAJAPAKSHA, S., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and MADZUDZO, G. 2023. Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system. Journal of information security and applications [online], 77, article number 103570. Available from: https://doi.org/10.1016/j.jisa.2023.103570

Modern automobiles are equipped with a large number of electronic control units (ECUs) to provide safe driver assistance and comfortable services. The controller area network (CAN) provides near real-time data transmission between ECUs with adequate... Read More about Beyond vanilla: improved autoencoder-based ensemble in-vehicle intrusion detection system..

Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets. (2023)
Journal Article
FU, H., SUN, G., ZHANG, L., ZHANG, A., REN, J., JIA, X. and LI, F. 2023. Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets. ISPRS journal of photogrammetry and remote sensing [online], 203, pages 115-134. Available from: https://doi.org/10.1016/j.isprsjprs.2023.07.013

The precise classification of land covers with hyperspectral imagery (HSI) is a major research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) systems as the abundant data sources have brought severe intra-class spectr... Read More about Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets..

Singular spectrum analysis method for hyperspectral imagery feature extraction: a review and evaluation. (2023)
Journal Article
SUN, G., FU, H., ZHANG, A. and REN, J. 2023. Singular spectrum analysis method for hyperspectral imagery feature extraction: a review and evaluation. Cehui xuebao/Acta geodaetica et cartographica sinica [online], 15(7), pages 1148-1163. Available from: https://doi.org/10.11947/j.AGCS.2023.20220542

Hyperspectral remote sensing imagery (HSI) usually contains dozens to hundreds of continuous spectral bands, with the syncretism of spectrum and image, spectral continuity, which can realize fine classification of ground objects and has been widely u... Read More about Singular spectrum analysis method for hyperspectral imagery feature extraction: a review and evaluation..

An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method. (2023)
Journal Article
LI, J.W., LIN, D., CHE, Y., LV, J.J., CHEN, R.J., WANG, L.J., ZENG, X.X., REN, J.C., ZHAO, H.M. and LU, X. 2023. An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method. Frontiers in neuroscience [online], 17, article 1221512. Available from: https://doi.org/10.3389/fnins.2023.1221512

Efficiently recognizing emotions is a critical pursuit in brain–computer interface (BCI), as it has many applications for intelligent healthcare services. In this work, an innovative approach inspired by the genetic code in bioinformatics, which util... Read More about An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method..

MCCFNet: multi-channel color fusion network for cognitive classification of traditional Chinese paintings. (2023)
Journal Article
GENG, J., ZHANG, X., YAN, Y., SUN, M., ZHANG, H., ASSAAD, M., REN, J. and LI, X. 2023. MCCFNet: multi-channel color fusion network for cognitive classification of traditional Chinese paintings. Cognitive computation [online], In Press. Available from: https://doi.org/10.1007/s12559-023-10172-1

The computational modeling and analysis of traditional Chinese painting rely heavily on cognitive classification based on visual perception. This approach is crucial for understanding and identifying artworks created by different artists. However, th... Read More about MCCFNet: multi-channel color fusion network for cognitive classification of traditional Chinese paintings..

Large kernel spectral and spatial attention networks for hyperspectral image classification. (2023)
Journal Article
SUN, G., PAN, Z., ZHANG, A., JIA, X., REN, J., FU, H. and YAN, K. 2023. Large kernel spectral and spatial attention networks for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], In Press. Available from: https://doi.org/10.1109/tgrs.2023.3292065

Currently, long-range spectral and spatial dependencies have been widely demonstrated to be essential for hyperspectral image (HSI) classification. Due to the transformer superior ability to exploit long-range representations, the transformer-based m... Read More about Large kernel spectral and spatial attention networks for hyperspectral image classification..

Advances in structural analysis and process monitoring of thermoplastic composite pipes. (2023)
Journal Article
OKOLIE, O., LATTO, J., FAISAL, N., JAMIESON, H., MUKHERJI, A. and NJUGUNA, J. 2023. Advances in structural analysis and process monitoring of thermoplastic composite pipes. Heliyon [online], 9(7), e17918. Available from: https://doi.org/10.1016/j.heliyon.2023.e17918

Thermoplastic composite pipes (TCP) in comparison to other pipes have proven beneficial features due to its flexibility which includes being fit for purpose, lightweight and no corrosion. However, during the manufacturing of TCP which involves the co... Read More about Advances in structural analysis and process monitoring of thermoplastic composite pipes..

DEFEG: deep ensemble with weighted feature generation. (2023)
Journal Article
LUONG, A.V., NGUYEN, T.T., HAN, K., VU, T.H., MCCALL, J. and LIEW, A.W.-C. 2023. DEFEG: deep ensemble with weighted feature generation. Knowledge-based systems [online], 275, article 110691. Available from: https://doi.org/10.1016/j.knosys.2023.110691

With the significant breakthrough of Deep Neural Networks in recent years, multi-layer architecture has influenced other sub-fields of machine learning including ensemble learning. In 2017, Zhou and Feng introduced a deep random forest called gcFores... Read More about DEFEG: deep ensemble with weighted feature generation..

Self-attention enhanced deep residual network for spatial image steganalysis. (2023)
Journal Article
XIE, G., REN, J., MARSHALL, S., ZHAO, H., LI, R. and CHEN, R. 2023. Self-attention enhanced deep residual network for spatial image steganalysis. Digital signal processing [online], 139, article 104063. Available from: https://doi.org/10.1016/j.dsp.2023.104063

As a specially designed tool and technique for the detection of image steganography, image steganalysis conceals information under the carriers for covert communications. Being developed on the BOSSbase dataset and released a decade ago, most of the... Read More about Self-attention enhanced deep residual network for spatial image steganalysis..

Person recognition based on deep gait: a survey. (2023)
Journal Article
KHALILUZZAMAN, M., UDDIN, A., DEB, K. and HASAN, M.J. 2023. Person recognition based on deep gait: a survey. Sensors [online], 23(10), article 4875. Available from: https://doi.org/10.3390/s23104875

Gait recognition, also known as walking pattern recognition, has expressed deep interest in the computer vision and biometrics community due to its potential to identify individuals from a distance. It has attracted increasing attention due to its po... Read More about Person recognition based on deep gait: a survey..

CBANet: an end-to-end cross band 2-D attention network for hyperspectral change detection in remote sensing. (2023)
Journal Article
LI, Y., REN, J., YAN, Y., LIU, Q., MA, P., PETROVSKI, A. and SUN, H. 2023. CBANet: an end-to-end cross band 2-D attention network for hyperspectral change detection in remote sensing. IEEE transactions on geoscience and remote sensing [online], 61, 5513011. Available from: https://doi.org/10.1109/TGRS.2023.3276589

As a fundamental task in remote sensing observation of the earth, change detection using hyperspectral images (HSI) features high accuracy due to the combination of the rich spectral and spatial information, especially for identifying land-cover vari... Read More about CBANet: an end-to-end cross band 2-D attention network for hyperspectral change detection in remote sensing..

H-RNet: hybrid relation network for few-shot learning-based hyperspectral image classification. (2023)
Journal Article
LIU, X., DONG, Z., LI, H., REN, J., ZHAO, H., LI, H., CHEN, W. and XIAO, Z. 2023. H-RNet: hybrid relation network for few-shot learning-based hyperspectral image classification. Remote sensing [online], 15(10), article 2497. Available from: https://doi.org/10.3390/rs15102497

Deep network models rely on sufficient training samples to perform reasonably well, which has inevitably constrained their application in classification of hyperspectral images (HSIs) due to the limited availability of labeled data. To tackle this pa... Read More about H-RNet: hybrid relation network for few-shot learning-based hyperspectral image classification..

Tensor singular spectral analysis for 3D feature extraction in hyperspectral images. (2023)
Journal Article
FU, H., SUN, G., ZHANG, A., SHAO, B., REN, J. and JIA, X. 2023. Tensor singular spectral analysis for 3D feature extraction in hyperspectral images. IEEE transactions on geoscience and remote sensing [online], 61, article 5403914. Available from: https://doi.org/10.1109/TGRS.2023.3272669

Due to the cubic structure of a hyperspectral image (HSI), how to characterize its spectral and spatial properties in three dimensions is challenging. Conventional spectral-spatial methods usually extract spectral and spatial information separately,... Read More about Tensor singular spectral analysis for 3D feature extraction in hyperspectral images..

Rethinking densely connected convolutional networks for diagnosing infectious diseases. (2023)
Journal Article
PODDER, P., ALAM, F.B., MONDAL, M.R.H., HASAN, M.J., ROHAN, A. and BHARATI, S. 2023. Rethinking densely connected convolutional networks for diagnosing infectious diseases. Computers [online], 12(5), article 95. Available from: https://doi.org/10.3390/computers12050095

Due to its high transmissibility, the COVID-19 pandemic has placed an unprecedented burden on healthcare systems worldwide. X-ray imaging of the chest has emerged as a valuable and cost-effective tool for detecting and diagnosing COVID-19 patients. I... Read More about Rethinking densely connected convolutional networks for diagnosing infectious diseases..

Data-driven solution to identify sentiments from online drug reviews. (2023)
Journal Article
HAQUE, R., LASKAR, S.H., KHUSHBU, K.G., HASAN, M.J. and UDDIN, J. 2023. Data-driven solution to identify sentiments from online drug reviews. Computers [online], 12(4), article 87. Available from: https://doi.org/10.3390/computers12040087

With the proliferation of the internet, social networking sites have become a primary source of user-generated content, including vast amounts of information about medications, diagnoses, treatments, and disorders. Comments on previously used medicin... Read More about Data-driven solution to identify sentiments from online drug reviews..

Rapid detection of multi-QR codes based on multistage stepwise discrimination and a compressed mobilenet. (2023)
Journal Article
CHEN, R., HUANG, H., YU, Y., REN, J., WANG, P., ZHAO, H. and LU, X. 2023. Rapid detection of multi-QR codes based on multistage stepwise discrimination and a compressed mobilenet. IEEE internet of things journal [online], Early Access. Available from: https://doi.org/10.1109/JIOT.2023.3268636

Poor real-time performance in multi-QR codes detection has been a bottleneck in QR code decoding based Internet-of-Things (IoT) systems. To tackle this issue, we propose in this paper a rapid detection approach, which consists of Multistage Stepwise... Read More about Rapid detection of multi-QR codes based on multistage stepwise discrimination and a compressed mobilenet..

A comparative study of anomaly detection methods for gross error detection problems. (2023)
Journal Article
DOBOS, D., NGUYEN, T.T., DANG, T., WILSON, A., CORBETT, H., MCCALL, J. and STOCKTON, P. 2023. A comparative study of anomaly detection methods for gross error detection problems. Computers and chemical engineering [online], 175, article 108263. Available from: https://doi.org/10.1016/j.compchemeng.2023.108263

The chemical industry requires highly accurate and reliable measurements to ensure smooth operation and effective monitoring of processing facilities. However, measured data inevitably contains errors from various sources. Traditionally in flow syste... Read More about A comparative study of anomaly detection methods for gross error detection problems..

Plug and abandonment of oil and gas wells: a comprehensive review of regulations, practices, and related impact of materials selection. (2023)
Journal Article
CHUKWUEMEKA, A.O., OLUYEMI, G., MOHAMMED, A.I. and NJUGUNA, J. 2023. Plug and abandonment of oil and gas wells: a comprehensive review of regulations, practices, and related impact of materials selection. Geoenergy science and engineering [online], 226, article 211718. Available from: https://doi.org/10.1016/j.geoen.2023.211718

This paper reviews the state of research in permanent barrier materials for plug and abandonment of oil and gas wells to identify key strengths and weaknesses of each barrier material and understand the impact of reservoir conditions and fluids on ba... Read More about Plug and abandonment of oil and gas wells: a comprehensive review of regulations, practices, and related impact of materials selection..