All Outputs (30)

Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies. (2024)
Presentation / Conference Contribution
HASAN, M.J., ELYAN, E., YAN, Y., REN, J. and SARKER, M.M.K. 2024. Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies. In Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th International conference on Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 220-228. Available from: https://doi.org/10.1007/978-981-97-1417-9_21

Retrofitting and thermographic survey (TS) companies in Scotland collaborate with social housing providers to tackle fuel poverty. They employ ground-level infrared (IR) camera-based-TSs (GIRTSs) for collecting thermal images to identify the heat los... Read More about Segmentation framework for heat loss identification in thermal images: empowering Scottish retrofitting and thermographic survey companies..

Nondestructive quantitative measurement for precision quality control in additive manufacturing using hyperspectral imagery and machine learning. (2024)
Journal Article
YAN, Y., REN, J., SUN, H. and WILLIAMS, R. 2024. Nondestructive quantitative measurement for precision quality control in additive manufacturing using hyperspectral imagery and machine learning. IEEE transactions on industrial informatics [online], 20(8), pages 9963-9975. Available from: https://doi.org/10.1109/TII.2024.3384609

Measuring the purity of the metal powder is essential to maintain the quality of additive manufacturing products. Contamination is a significant concern, leading to cracks and malfunctions in the final products. Conventional assessment methods focus... Read More about Nondestructive quantitative measurement for precision quality control in additive manufacturing using hyperspectral imagery and machine learning..

Siamese residual neural network for musical shape evaluation in piano performance assessment. (2023)
Presentation / Conference Contribution
LI, X., WEISS, S., YAN, Y., LI, Y., REN, J., SORAGHAN, J. and GONG, M. 2023. Siamese residual neural network for musical shape evaluation in piano performance assessment. In Proceedings of the 31st European signal processing conference 2023 (EUSIPCO 2023), 4-8 September 2023, Helsinki, Finland. Piscataway: IEEE [online], pages 216-220. Available from: https://doi.org/10.23919/EUSIPCO58844.2023.10289901

Understanding and identifying musical shape plays an important role in music education and performance assessment. To simplify the otherwise time- and cost-intensive musical shape evaluation, in this paper we explore how artificial intelligence (AI)... Read More about Siamese residual neural network for musical shape evaluation in piano performance assessment..

Hyperspectral imaging based corrosion detection in nuclear packages. (2023)
Journal Article
ZABALZA, J., MURRAY, P., BENNETT, S., CAMPBELL, A.J., MARSHALL, S., REN, J., YAN, Y., BERNARD, R., HEPWORTH, S., MALONE, S., COCKBAIN, N., OFFIN, D. and HOLLIDAY, C. 2023. Hyperspectral imaging based corrosion detection in nuclear packages. IEEE sensors journal [online], 23(21), pages 25607-25617. Available from: https://doi.org/10.1109/jsen.2023.3312938

In the Sellafield nuclear site, intermediate level waste and special nuclear material is stored above ground in stainless steel packages or containers, with thousands expected to be stored for several decades before permanent disposal in a geological... Read More about Hyperspectral imaging based corrosion detection in nuclear packages..

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..

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..

Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset] (2023)
Data
MA, P., REN, J., SUN, G., ZHAO, H., JIA, X., YAN, Y. and ZABALZA, J. 2023. Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset]. IEEE transactions on geoscience and remote sensing [online], 61, article 5508912. Available from: https://doi.org/10.1109/tgrs.2023.3260634/mm1

In this paper, we have proposed Multiscale Superpixelwise Prophet model (MSPM), a novel spectral-spatial feature mining framework for noise-robust feature extraction and effective data classification of the HSI. First, we demonstrate that the Prophet... Read More about Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. [Dataset].

Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. (2023)
Journal Article
MA, P., REN, J., SUN, G., ZHAO, H., JIA, X., YAN, Y. and ZABALZA, J. 2023. Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images. IEEE transactions on geoscience and remote sensing [online], 61, article 5508912. Available from: https://doi.org/10.1109/TGRS.2023.3260634

Despite of various approaches proposed to smooth the hyperspectral images (HSIs) before feature extraction, the efficacy is still affected by the noise, even using the corrected dataset with the noisy and water absorption bands discarded. In this stu... Read More about Multiscale superpixelwise prophet model for noise-robust feature extraction in hyperspectral images..

Composite repair and remanufacturing. (2022)
Book Chapter
VON FREEDEN, J., DE WIT, J., CABA, S., KROLL, S., ZHAO, H., REN, J., YAN, Y., ARSHED, F., AHMAD, A. and XIROUCHAKIS, P. 2022. Composite repair and remanufacturing. In Colledani, M. and Turri, S. (eds.) Systemic circular economy solutions for fiber reinforced composites. Cham: Springer [online], pages 191-214. Available from: https://doi.org/10.1007/978-3-031-22352-5_10

For the reuse of components and structures made of fiber composite materials, a complete remanufacturing process chain is necessary to prepare the parts for a further life cycle. The first step is to dismantle the parts to be reused. Fiber composite... Read More about Composite repair and remanufacturing..

Digital condition monitoring for wider blue economy. (2022)
Presentation / Conference Contribution
HASAN, M.J., YAN, Y. and REN, J. 2022. Digital condition monitoring for wider blue economy. Presented at the 12th Annual science meeting of the Marine Alliance for Science and Technology for Scotland (MASTS ASM 2022), 8-10 November 2022, Glasgow, UK.

In the process of decommissioning energy systems, condition monitoring is crucial. It can make the health status of offshore oil and gas installations, pipelines, wind farms etc. transparent to policymakers and stakeholders, and aid them in creating... Read More about Digital condition monitoring for wider blue economy..

Crowdsourced quality assessment of enhanced underwater images: a pilot study. (2022)
Presentation / Conference Contribution
LIN, H., MEN, H., YAN, Y., REN, J. and SAUPE, D. 2022. Crowdsourced quality assessment of enhanced underwater images: a pilot study. In Proceedings of 14th International conference on quality of multimedia experience 2022 (QoMEX 2022), 5-7 September 2022, Lippstadt, Germany. Piscataway: IEEE [online], article 9900904. Available from: https://doi.org/10.1109/QoMEX55416.2022.9900904

Underwater image enhancement (UIE) is essential for a high-quality underwater optical imaging system. While a number of UIE algorithms have been proposed in recent years, there is little study on image quality assessment (IQA) of enhanced underwater... Read More about Crowdsourced quality assessment of enhanced underwater images: a pilot study..

Printed texture guided color feature fusion for impressionism style rendering of oil paintings. (2022)
Journal Article
GENG, J., MA, L., LI, X., ZHANG, X. and YAN, Y. 2022. Printed texture guided color feature fusion for impressionism style rendering of oil paintings. Mathematics [online], 10(19): advances in computer vision and machine learning, article 3700. Available from: https://doi.org/10.3390/math10193700

As a major branch of Non-Photorealistic Rendering (NPR), image stylization mainly uses computer algorithms to render a photo into an artistic painting. Recent work has shown that the ex-traction of style information such as stroke texture and color o... Read More about Printed texture guided color feature fusion for impressionism style rendering of oil paintings..

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..

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..

Unsupervised change detection in hyperspectral images using principal components space data clustering. (2022)
Presentation / Conference Contribution
LI, Y., REN, J., YAN, Y., LIU, Q., PETROVSKI, A. and MCCALL, J. 2022. Unsupervised change detection in hyperspectral images using principal components space data clustering. Journal of physics: conference series [online], 2278: proceedings of the 6th International conference on machine vision and information technology (CMVIT 2022), 25 February 2022, [virtual event], article number 012021. Available from: https://doi.org/10.1088/1742-6596/2278/1/012021

Change detection of hyperspectral images is a very important subject in the field of remote sensing application. Due to the large number of bands and the high correlation between adjacent bands in the hyperspectral image cube, information redundancy... Read More about Unsupervised change detection in hyperspectral images using principal components space data clustering..

Multi-sourced sensing and support vector machine classification for effective detection of fire hazard in early stage. (2022)
Journal Article
CHEN, S., REN, J., YAN, Y., SUN, M., HU, F. and ZHAO, H. 2022. Multi-sourced sensing and support vector machine classification for effective detection of fire hazard in early stage. Computers and electrical engineering [online], 101, article 108046. Available from: https://doi.org/10.1016/j.compeleceng.2022.108046

Accurate detection and early warning of fire hazard are crucial for reducing the associated damages. Due to the limitations of smoke-based detection mechanism, most commercial detectors fail to distinguish the smoke from dust and steam, leading to fr... Read More about Multi-sourced sensing and support vector machine classification for effective detection of fire hazard in early stage..

Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. (2022)
Presentation / Conference Contribution
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)
Presentation / Conference Contribution
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..

Non-destructive testing of composite fibre materials with hyperspectral imaging: evaluative studies in the EU H2020 FibreEUse project. (2022)
Journal Article
YAN, Y., REN, J., ZHAO, H., WINDMILL, J.F.C., IJOMAH, W., DE WIT, J. and VON FREEDEN, J. 2022. Non-destructive testing of composite fibre materials with hyperspectral imaging: evaluative studies in the EU H2020 FibreEUse project. IEEE transactions on instrumentation and measurement [online], 71, article 6002213. Available from: https://doi.org/10.1109/TIM.2022.3155745

Through capturing spectral data from a wide frequency range along with the spatial information, hyperspectral imaging (HSI) can detect minor differences in terms of temperature, moisture and chemical composition. Therefore, HSI has been successfully... Read More about Non-destructive testing of composite fibre materials with hyperspectral imaging: evaluative studies in the EU H2020 FibreEUse project..

PCA-domain fused singular spectral analysis for fast and noise-robust spectral-spatial feature mining in hyperspectral classification. (2021)
Journal Article
YAN, Y., REN, J., LIU, Q., ZHAO, H., SUN, H. and ZABALZA, J. 2023. PCA-domain fused singular spectral analysis for fast and noise-robust spectral-spatial feature mining in hyperspectral classification. IEEE geoscience and remote sensing letters [online], 20, article 5505405. Available from: https://doi.org/10.1109/LGRS.2021.3121565

The principal component analysis (PCA) and 2-D singular spectral analysis (2DSSA) are widely used for spectral domain and spatial domain feature extraction in hyperspectral images (HSI). However, PCA itself suffers from low efficacy if no spatial inf... Read More about PCA-domain fused singular spectral analysis for fast and noise-robust spectral-spatial feature mining in hyperspectral classification..