All Outputs (151)

PWDformer: deformable transformer for long-term series forecasting. (2023)
Journal Article
WANG, Z., RAN, H., REN, J. and SUN, M. 2024. PWDformer: deformable transformer for long-term series forecasting. Pattern recognition [online], 147, article number 110118. Available from: https://doi.org/10.1016/j.patcog.2023.110118

Long-term forecasting is of paramount importance in numerous scenarios, including predicting future energy, water, and food consumption. For instance, extreme weather events and natural disasters can profoundly impact infrastructure operations and po... Read More about PWDformer: deformable transformer for long-term series forecasting..

Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspectral imaging. (2023)
Journal Article
TANG, Y., YANG, J., ZHUANG, J., HOU, C., MIAO, A., REN, J., HUANG, H., TAN, Z. and PALIWAL, J. 2023. Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspecral imaging. Computers and electronics in agriculture [online], 214, article number 108348. Available from: https://doi.org/10.1016/j.compag.2023.108348

Citrus fruit are susceptible to Colletotrichum gloeosporioides infestation during postharvest and shelf storage. Early and accurate detection of citrus anthracnose is conducive for carrying out targeted pesticide control and mitigating the potential... Read More about Early detection of citrus anthracnose caused by Colletotrichum gloeosporioides using hyperspectral imaging..

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..

Effective detection of seismic events by non-classical receptive field visual cognitive modelling. (2023)
Journal Article
ZHAO, J., LEI, HAOJIE, LI, YANG, REN, J., SUN, G., ZHAO, H., SHEN, H. and WANG, D. 2023. Effective detection of seismic events by non-classical receptive field visual cognitive modelling. Journal of seismic exploration [online], 32(4), pages 385-406. Available from: http://www.geophysical-press.com/online/Vol32-4_art6.pdf

The detection and up-picking of the seismic events are critical for seismic data analysis and interpretation. Events picking can be used for sequence stratigraphic analysis, reservoir feature extraction, the determining of the subsequent reflection i... Read More about Effective detection of seismic events by non-classical receptive field visual cognitive modelling..

Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets. (2023)
Journal Article
FU, H., SUN, G., ZHANG, L., ZHANG, A., REN, J., JIA, X. and LI, F. 2023. Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets. ISPRS journal of photogrammetry and remote sensing [online], 203, pages 115-134. Available from: https://doi.org/10.1016/j.isprsjprs.2023.07.013

The precise classification of land covers with hyperspectral imagery (HSI) is a major research-focused topic in remote sensing, especially using unmanned aerial vehicle (UAV) systems as the abundant data sources have brought severe intra-class spectr... Read More about Three-dimensional singular spectrum analysis for precise land cover classification from UAV-borne hyperspectral benchmark datasets..

An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method. (2023)
Journal Article
LI, J.W., LIN, D., CHE, Y., LV, J.J., CHEN, R.J., WANG, L.J., ZENG, X.X., REN, J.C., ZHAO, H.M. and LU, X. 2023. An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method. Frontiers in neuroscience [online], 17, article 1221512. Available from: https://doi.org/10.3389/fnins.2023.1221512

Efficiently recognizing emotions is a critical pursuit in brain–computer interface (BCI), as it has many applications for intelligent healthcare services. In this work, an innovative approach inspired by the genetic code in bioinformatics, which util... Read More about An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method..

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..

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..

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..

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..

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..

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..

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..

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..

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..