All Outputs (30)

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..

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. (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..

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].

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..

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..

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..

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..

Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning. (2021)
Journal Article
YAN, Y., REN, J., TSCHANNERL, J., ZHAO, H., HARRISON, B. and JACK, F. 2021. Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning. IEEE transactions on instrumentation and measurement [online], 70, article 5010715. Available from: https://doi.org/10.1109/TIM.2021.3082274

Quantifying phenolic compound in peated barley malt and discriminating its origin are essential to maintain the aroma of high-quality Scottish whisky during the manufacturing process. The content of the total phenol varies in peated barley malts, whi... Read More about Nondestructive phenolic compounds measurement and origin discrimination of peated barley malt using near-infrared hyperspectral imagery and machine learning..

Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images. (2020)
Journal Article
CHAI, Y., REN, J., HWANG, B., WANG, J., FAN, D., YAN, Y. and ZHU, S. 2021. Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 577-586. Available from: https://doi.org/10.1109/jstars.2020.3040614

Efficient and accurate segmentation of sea ice floes from high-resolution optical (HRO) remote sensing images is crucial for understanding of sea ice evolutions and climate changes, especially in coping with the large data volume. Existing methods su... Read More about Texture-sensitive superpixeling and adaptive thresholding for effective segmentation of sea ice floes in high-resolution optical images..

Generic wavelet‐based image decomposition and reconstruction framework for multi‐modal data analysis in smart camera applications. (2020)
Journal Article
YAN, Y., LIU, Y., YANG, M., ZHAO, H., CHAI, Y. and REN, J. 2020. Generic wavelet-based image decomposition and reconstruction framework for multi-modal data analysis in smart camera applications. IET computer vision [online], 14(7): computer vision for smart cameras and camera networks, pages 471-479. Available from: https://doi.org/10.1049/iet-cvi.2019.0780

Effective acquisition, analysis and reconstruction of multi-modal data such as colour and multi-/hyper-spectral imagery is crucial in smart camera applications, where wavelet-based coding and compression of images are highly demanded. Many existing d... Read More about Generic wavelet‐based image decomposition and reconstruction framework for multi‐modal data analysis in smart camera applications..

A novel intelligent computational approach to model epidemiological trends and assess the impact of non-pharmacological interventions for COVID-19. (2020)
Journal Article
REN, J., YAN, Y., ZHAO, H., MA, P., ZABALZA, J., HUSSAIN, Z., LUO, S., DAI, Q., ZHAO, S., SHEIKH, A., HUSSAIN, A. and LI, H. 2020. A novel intelligent computational approach to model epidemiological trends and assess the impact of non-pharmacological interventions for COVID-19. IEEE Journal of biomedical and health informatics [online], 24(12), pages 3551-3563. Available from: https://doi.org/10.1109/jbhi.2020.3027987

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public health. It is crucial we understand the epidemiological trends and impact of non-pharmacological interventions (NPIs), such as lockdowns for effective mana... Read More about A novel intelligent computational approach to model epidemiological trends and assess the impact of non-pharmacological interventions for COVID-19..

Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study. (2019)
Journal Article
ZABALZA, J., FEI, Z., WONG, C., YAN, Y., MINEO, C., YANG, E., RODDEN, T., MEHNEN, J., PHAM, Q.-C. and REN, J. 2019. Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study. Sensors [online], 19(6), article 1354. Available from: https://doi.org/10.3390/s19061354

Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a c... Read More about Smart sensing and adaptive reasoning for enabling industrial robots with interactive human-robot capabilities in dynamic environments: a case study..

Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images. (2019)
Journal Article
SUN, H., REN, J., ZHAO, H., YAN, Y., ZABALZA, J. and MARSHALL, S. 2019. Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images. Remote sensing [online], 11(5), article 536. Available from: https://doi.org/10.3390/rs11050536

To improve the performance of the sparse representation classification (SRC), we propose a superpixel-based feature specific sparse representation framework (SPFS-SRC) for spectral-spatial classification of hyperspectral images (HSI) at superpixel le... Read More about Superpixel based feature specific sparse representation for spectral-spatial classification of hyperspectral images..