Immersive innovations for the communication of heritage, handcraft and sustainability. (2023)
Journal Article
CROSS, K., MESJAR, L., STEED, J. and JIANG, Y. [2023]. Immersive innovations for the communication of heritage, handcraft and sustainability. International journal of fashion design, technology and education [online], Latest Articles. Available from: https://doi.org/10.1080/17543266.2023.2277264

Textile and fashion brands convey core values through marketing, and in slow-fashion heritage brands this often includes skilled craftsmanship, authenticity, sustainability and provenance. As industry digitalisation continues, brands are employing im... Read More about Immersive innovations for the communication of heritage, handcraft and sustainability..

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..

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..

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..

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..

On the elusivity of dynamic optimisation problems. (2023)
Journal Article
ALZA, J., BARTLETT, M., CEBERIO, J. and MCCALL, J. 2023. On the elusivity of dynamic optimisation problems. Swarm and evolutionary computation [online], 78, article 101289. Available from: https://doi.org/10.1016/j.swevo.2023.101289

The field of dynamic optimisation continuously designs and compares algorithms with adaptation abilities that deal with changing problems during their search process. However, restarting the search algorithm after a detected change is sometimes a bet... Read More about On the elusivity of dynamic optimisation problems..

Contour extraction of medical images using an attention-based network. (2023)
Journal Article
LV, J.J., CHEN, H.Y., LI, J.W., LIN, K.H., CHEN, R.J., WANG, L.J., ZENG, X.X., REN, J.C. and ZHAO, H.M. 2023. Contour extraction of medical images using an attention-based network. Biomedical signal processing and control [online], 84, article 104828. Available from: https://doi.org/10.1016/j.bspc.2023.104828

A comprehensive analysis of medical images is important, as it assists in early screening and clinical treatment as well as subsequent rehabilitation. In general, the contour information can elaborately describe the shape and size of lesions in a med... Read More about Contour extraction of medical images using an attention-based network..

The intersection of fashion, immersive technology and sustainability: a literature review. (2023)
Journal Article
MESJAR, L., CROSS, K., JIANG, Y. and STEED, J. 2023. The intersection of fashion, immersive technology and sustainability: a literature review. Sustainability [online], 15(4), article number 3761. Available from: https://doi.org/10.3390/su15043761

Fashion industry emissions, resource use and waste are attracting increasing consumer and government attention, with broad agreement that a new approach is required along the supply chain. Following the COVID-19 pandemic, a move to digitalisation fac... Read More about The intersection of fashion, immersive technology and sustainability: a literature review..

PSSA: PCA-domain superpixelwise singular spectral analysis for unsupervised hyperspectral image classification. (2023)
Journal Article
LIU, Q., XUE, D., TANG, Y., ZHAO, Y., REN, J. and SUN, H. 2023. PSSA: PCA-domain superpixelwise singular spectral analysis for unsupervised hyperspectral image classification. Remote sensing [online], 15(4), article 890. Available from: https://doi.org/10.3390/rs15040890

Although supervised classification of hyperspectral images (HSI) has achieved success in remote sensing, its applications in real scenarios are often constrained, mainly due to the insufficiently available or lack of labelled data. As a result, unsup... Read More about PSSA: PCA-domain superpixelwise singular spectral analysis for unsupervised hyperspectral image classification..

Multiscale diff-changed feature fusion network for hyperspectral image change detection. (2023)
Journal Article
LUO, F., ZHOU, T., LIU, J., GUO, T., GONG, X. and REN, J. 2023. Multiscale diff-changed feature fusion network for hyperspectral image change detection. IEEE transactions on geoscience and remote sensing [online], 61, article 5502713. Available from: https://doi.org/10.1109/TGRS.2023.3241097

For hyperspectral images (HSI) change detection (CD), multi-scale features are usually used to construct the detection models. However, the existing studies only consider the multi-scale features containing changed and unchanged components, which is... Read More about Multiscale diff-changed feature fusion network for hyperspectral image change detection..

Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation. (2023)
Journal Article
SUN, M., LI, P., REN, J. and WANG, Z. 2023. Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation. Cognitive computation [online], 15(1), pages 348-358. Available from: https://doi.org/10.1007/s12559-022-10094-4

Existing deep learning–based medical image segmentation methods have achieved gratifying progress, but they still suffer from the coarse boundaries with similar pixels of target. Because the boundary of medical images becomes blurred and the gradient... Read More about Attention mechanism enhanced multi-layer edge perception network for deep semantic medical segmentation..

Efficient breast cancer classification network with dual squeeze and excitation in histopathological images. (2022)
Journal Article
SARKER, M.M.K., AKRAM, F., ALSHARID, M., SINGH, V.K., YASRAB, R. and ELYAN, E. 2023. Efficient breast cancer classification network with dual squeeze and excitation in histopathological images. Diagnostics [online], 13(1), article 103. Available from: https://doi.org/10.3390/diagnostics13010103

Medical image analysis methods for mammograms, ultrasound, and magnetic resonance imaging (MRI) cannot provide the underline features on the cellular level to understand the cancer microenvironment which makes them unsuitable for breast cancer subtyp... Read More about Efficient breast cancer classification network with dual squeeze and excitation in histopathological images..

An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification. (2022)
Journal Article
ZHAO, C., QIN, B., FENG, S., ZHU, W., ZHANG, L. and REN, J. 2022. An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5546216. Available from: https://doi.org/10.1109/TGRS.2022.3230378

Despite success in the same-scene hyperspectral image classification (HSIC), for the cross-scene classification, samples between source and target scenes are not drawn from the independent and identical distribution, resulting in significant performa... Read More about An unsupervised domain adaptation method towards multi-level features and decision boundaries for cross-scene hyperspectral image classification..

Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture. (2022)
Journal Article
HUANG, H., TANG, Y., TAN, Z., ZHUANG, J., HOU, C., CHEN, W. and REN, J. 2022. Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture. IEEE transactions on geoscience and remote sensing [online], 60, article number 4416013. Available from: https://doi.org/10.1109/TGRS.2022.3224580

Color calibration is a critical step for unmanned aerial vehicle (UAV) remote sensing, especially in precision agriculture, which relies mainly on correlating color changes to specific quality attributes, e.g. plant health, disease, and pest stresses... Read More about Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture..

Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures. (2022)
Journal Article
ZABALZA, J., MURRAY, P., MARSHALL, S., REN, J., BERNARD, R. and HEPWORTH, S. 2023. Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures. IEEE sensors journal [online], 23(1), pages 452-459. Available from: https://doi.org/10.1109/JSEN.2022.3221680

Traditionally, Special Nuclear Material (SNM) at Sellafield has been stored in multi-layered packages, consisting of metallic cans and an over-layer of plasticized Polyvinyl Chloride (PVC) as an intermediate layer when transitioning between areas of... Read More about Hyperspectral imaging based detection of PVC during Sellafield repackaging procedures..

A novel gradient-guided post-processing method for adaptive image steganography. (2022)
Journal Article
XIE, G., REN, J., MARSHALL, S., ZHAO, H. and LI, R. 2023. A novel gradient-guided post-processing method for adaptive image steganography. Signal processing [online], 203, article 108813. Available from: https://doi.org/10.1016/j.sigpro.2022.108813

Designing an effective cost function has always been the key in image steganography after the development of the near-optimal encoders. To learn the cost maps automatically, the Generative Adversarial Networks (GAN) are often trained from the given c... Read More about A novel gradient-guided post-processing method for adaptive image steganography..

Multiscale voting mechanism for rice leaf disease recognition under natural field conditions. (2022)
Journal Article
TANG, Y., ZHAO, J., HUANG, H., ZHUANG, J., TAN, Z., HOU, C., CHEN, W. and REN, J. 2022. Multiscale voting mechanism for rice leaf disease recognition under natural field conditions. International journal of intelligent systems [online], 37(12), pages 12169-12191. Available from: https://doi.org/10.1002/int.23081

Rice leaf disease (RLD) is one of the major factors that cause the decline in production, and the automatic recognition of such diseases under natural field conditions is of great significance for timely targeted rice management. Although many machin... Read More about Multiscale voting mechanism for rice leaf disease recognition under natural field conditions..