All Outputs (30)

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..

VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program. (2019)
Presentation / Conference Contribution
YAN, Y., ZHAO, S., FANG, Y., LIU, Y., CHEN, Z. and REN, J. 2020. VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program. In Ren, J., Hussain, A., Zhao, H., Huang, K., Zheng, J., Cai, J., Chen, R. and Xiao, Y. (eds.). 2020. Advances in brain inspired cognitive systems: proceedings of the 10th Brain inspired cognitive systems (BCIS) international conference 2019 (BCIS 2019), 13-14 July 2019, Guangzhou, China. Lecture notes in computer science, 11691. Cham: Springer [online], pages 283-292. Available from: https://doi.org/10.1007/978-3-030-39431-8_27

In this paper, we introduce a new concept in VIP-STB, a funded project through Agri-Tech in China: Newton Network+ (ATCNN), in developing feasible solutions towards scaling-up STB from village level to upper level via some generic models and systems.... Read More about VIP-STB farm: scale-up village to county/province level to support science and technology at backyard (STB) program..

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..

Video for pick&place study in AFRC project. [Dataset] (2019)
Data
YAN, Y., ZABALZA, J., MINEO, C., YANG, E., FEI, Z. and WANG, C. 2019. Video for pick&place study in AFRC project. [Dataset]. Hosted on Pureportal (University Strathclyde) [online]. Available from: https://doi.org/10.15129/4df22803-2cc4-4cce-9cea-509f88f1b504

In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to... Read More about Video for pick&place study in AFRC project. [Dataset].

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..

Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study. (2018)
Presentation / Conference Contribution
ZABALZA, J., FEI, Z., WONG, C., YAN, Y., MINEO, C., YANG, E., RODDEN, T., MEHNEN, J., PHAM, Q.-C. and REN, J. 2018. Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study. In Ren, J., Hussain, A., Zheng, J., Liu, C.-L., Lou, B., Zhao, H. and Zhao, X. (eds.) Advances in brain inspired cognitive systems: proceedings of 9th International conference on Brain inspired cognitive system 2018 (BICS2018), 7-8 July 2018, Xi'an, China. Lecture notes in computer science, 10989. Cham: Springer [online], pages 790-800. Available from: https://doi.org/10.1007/978-3-030-00563-4_77

In order to extend the abilities of current robots in industrial applications towards more autonomous and flexible manufacturing, this work presents an integrated system comprising real-time sensing, path-planning and control of industrial robots to... Read More about Making industrial robots smarter with adaptive reasoning and autonomous thinking for real-time tasks in dynamic environments: a case study..

Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement. (2018)
Journal Article
YAN, Y., REN, J., SUN, G., ZHAO, H., HAN, J., LI, X., MARSHALL, S. and ZHAN, J. 2018. Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement. Pattern recognition [online], 79, pages 65-78. Available from: https://doi.org/10.1016/j.patcog.2018.02.004

Visual attention is a kind of fundamental cognitive capability that allows human beings to focus on the region of interests (ROIs) under complex natural environments. What kind of ROIs that we pay attention to mainly depends on two distinct types of... Read More about Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement..