All Outputs (52)

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..

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],15(6), pages 2050-2061. 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..

Android code vulnerabilities early detection using AI-powered ACVED plugin. (2023)
Conference Proceeding
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and PIRAS, L. 2023. Android code vulnerabilities early detection using AI-powered ACVED plugin. In Atluri, V. and Ferrara, A.L. (eds.) Data and applications security and privacy XXXVII; proceedings of the 37th annual IFIP WG (International Federation for Information Processing Working Group) 11.3 Data and applications security and privacy 2023 (DBSec 2023), 19-21 July 2023, Sophia-Antipolis, France. Lecture notes in computer science (LNCS), 13942. Cham: Springer [online], pages 339-357. Available from: https://doi.org/10.1007/978-3-031-37586-6_20

During Android application development, ensuring adequate security is a crucial and intricate aspect. However, many applications are released without adequate security measures due to the lack of vulnerability identification and code verification at... Read More about Android code vulnerabilities early detection using AI-powered ACVED plugin..

Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models. (2023)
Conference Proceeding
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. In De Capitani di Vimercati, S. and Samarati, P. (eds.) Proceedings of the 20th International conference on security and cryptography, 10-12 July 2023, Rome, Italy, volume 1. Setúbal: SciTePress [online], pages 659-666. Available from: https://doi.org/10.5220/0012060400003555

Ensuring the security of Android applications is a vital and intricate aspect requiring careful consideration during development. Unfortunately, many apps are published without sufficient security measures, possibly due to a lack of early vulnerabili... Read More about Labelled Vulnerability Dataset on Android source code (LVDAndro) to develop AI-based code vulnerability detection models..

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], 61, article 5519915. 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..

A multi-objective evolutionary approach to discover explainability trade-offs when using linear regression to effectively model the dynamic thermal behaviour of electrical machines. (2023)
Journal Article
BANDA, T.M., ZĂVOIANU, A.-C., PETROVSKI, A., WÖCKINGER, D. and BRAMERDORFER, G. 2024. A multi-objective evolutionary approach to discover explainability trade-offs when using linear regression to effectively model the dynamic thermal behaviour of electrical machines. ACM transactions on evolutionary learning and optimization [online], 4(1), article number 3. Available from: https://doi.org/10.1145/3597618

Modelling and controlling heat transfer in rotating electrical machines is very important as it enables the design of assemblies (e.g., motors) that are efficient and durable under multiple operational scenarios. To address the challenge of deriving... Read More about A multi-objective evolutionary approach to discover explainability trade-offs when using linear regression to effectively model the dynamic thermal behaviour of electrical machines..

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..

Advanced persistent threats detection based on deep learning approach. (2023)
Conference Proceeding
EKE, H.N. and PETROVSKI, A. 2023. Advanced persistent threats detection based on deep learning approach. In Proceedings of the 6th IEEE (Institute of Electrical and Electronics Engineers) International conference on Industrial cyber physical systems international conference 2023 (ICPS 2023), 8-11 May 2023, Wuhan, China. Piscataway: IEEE [online], pages 1-10. Available from: https://doi.org/10.1109/ICPS58381.2023.10128062

Advanced Persistent Threats (APTs) have been a major challenge in securing both Information Technology (IT) and Operational Technology (OT) systems. APT is a sophisticated attack that masquerade their actions to navigates around defenses, breach netw... Read More about Advanced persistent threats detection based on deep learning approach..

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..

Bayesian optimized autoencoder for predictive maintenance of smart packaging machines. (2023)
Conference Proceeding
ARIFEEN, M. and PETROVSKI, A. 2023. Bayesian optimized autoencoder for predictive maintenance of smart packaging machines. In Proceedings of the 6th IEEE (Institute of Electrical and Electronics Engineers) International conference on Industrial cyber-physical systems 2023 (ICPS 2023), 8-11 May 2023, Wuhan, China. Piscataway: IEEE [online], 10128064. Available from: https://doi.org/10.1109/icps58381.2023.10128064

Smart packaging machines incorporate various components (blades, motors, films) to accomplish the packaging process and are involved in almost all types of the manufacturing industry. Proper maintenance and monitoring of the components over time can... Read More about Bayesian optimized autoencoder for predictive maintenance of smart packaging machines..

Ensemble common features technique for lightweight intrusion detection in industrial control system. (2023)
Conference Proceeding
OTOKWALA, U.J. and PETROVSKI, A. 2023. Ensemble common features technique for lightweight intrusion detection in industrial control system. In Proceedings of the 6th IEEE (Institute of Electrical and Electronics Engineers) International conference on Industrial cyber-physical systems 2023 (ICPS 2023), 8-11 May 2023, Wuhan, China. Piscataway: IEEE [online], 10128040. Available from: https://doi.org/10.1109/icps58381.2023.10128040

The integration of the Industrial Control System (ICS) with corporate intranets and the internet has exposed the previously isolated SCADA system to a wide range of cyber-attacks. Interestingly, the vulnerabilities in the Modbus protocol, with which... Read More about Ensemble common features technique for lightweight intrusion detection in industrial control system..

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], 10(18), pages 15966-15979. 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..