All Outputs (105)

IR-capsule: two-stream network for face forgery detection. (2022)
Journal Article
LIN, K., HAN, W., LI, S., GU, Z., ZHAO, H., REN, J., ZHU, L. and LV, J. 2023 IR-capsule: two-stream network for face forgery detection. Cognitive computation [online], 15(1), pages 13-22. Available from: https://doi.org/10.1007/s12559-022-10008-4

With the emergence of deep learning, generating forged images or videos has become much easier in recent years. Face forgery detection, as a way to detect forgery, is an important topic in digital media forensics. Despite previous works having made r... Read More about IR-capsule: two-stream network for face forgery detection..

SC2Net: a novel segmentation-based classification network for detection of COVID-19 in chest X-ray images. (2022)
Journal Article
ZHAO, H., FANG, Z., REN, J., MACLELLAN, C., XIA, Y., SUN, M. and REN, K. 2022. SC2Net: a novel segmentation-based classification network for detection of COVID-19 in chest X-ray images. IEEE journal of biomedical and health informatics [online], 26(8), pages 4032-4043. Available from: https://doi.org/10.1109/JBHI.2022.3177854

The pandemic of COVID-19 has become a global crisis in public health, which has led to a massive number of deaths and severe economic degradation. To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial. As the popularly u... Read More about SC2Net: a novel segmentation-based classification network for detection of COVID-19 in chest X-ray images..

Multi-scale spatial fusion and regularization induced unsupervised auxiliary task CNN model for deep super-resolution of hyperspectral image. (2022)
Journal Article
HA, V.K., REN, J., WANG, Z., SUN, G., ZHAO, H. and MARSHALL, S. 2022. Multi-scale spatial fusion and regularization induced unsupervised auxiliary task CNN model for deep super-resolution of hyperspectral image. IEEE journal of selected topics in applied earth observations and remote sensing [online], 15, pages 4583-4598. Available from: https://doi.org/10.1109/JSTARS.2022.3176969

Hyperspectral images (HSI) features rich spectral information in many narrow bands but at a cost of a relatively low spatial resolution. As such, various methods have been developed for enhancing the spatial resolution of the low-resolution HSI (Lr-H... Read More about Multi-scale spatial fusion and regularization induced unsupervised auxiliary task CNN model for deep super-resolution of hyperspectral image..

Novel hyperbolic clustering-based band hierarchy (HCBH) for effective unsupervised band selection of hyperspectral images. (2022)
Journal Article
SUN, H., ZHANG, L., REN, J. and HUANG, H. 2022. Novel hyperbolic clustering-based band hierarchy (HCBH) for effective unsupervised band selection of hyperspectral images. Pattern recognition [online], 130, article number 108788. Available from: https://doi.org/10.1016/j.patcog.2022.108788

For dimensionality reduction of HSI, many clustering-based unsupervised band selection (UBS) methods have been proposed due to their superiority of reducing the high redundancy between selected bands. However, most of these methods fail to reflect th... Read More about Novel hyperbolic clustering-based band hierarchy (HCBH) for effective unsupervised band selection of hyperspectral images..

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..

Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification. (2022)
Journal Article
ZHANG, A., PAN, Z., FU, H., SUN, G., RONG, J., REN, J., JIA, X. and YAO, Y. 2022. Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification. Remote sensing [online], 14(9), article 2125. Available from: https://doi.org/10.3390/rs14092125

Joint sparse representation classification (JSRC) is a representative spectral–spatial classifier for hyperspectral images (HSIs). However, the JSRC is inappropriate for highly heterogeneous areas due to the spatial information being extracted from a... Read More about Superpixel nonlocal weighting joint sparse representation for hyperspectral image classification..

MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. (2022)
Journal Article
LI, M., WANG, Z., REN, J. and SUN, M. 2022. MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi‑type feature–based strong generalization. Cognitive computation [online], 14(4), pages 1435-1445. Available from: https://doi.org/10.1007/s12559-021-09947-1

With the increasing popularity of short videos on various social media platforms, there is a great challenge for evaluating the aesthetic quality of these videos. In this paper, we first construct a large-scale and properly annotated short video aest... Read More about MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization..

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..

PS-net: progressive selection network for salient object detection. (2022)
Journal Article
REN, J., WANG, Z. and REN, J. 2022. PS-net: progressive selection network for salient object detection. Cognitive computation [online], 14(2), pages 794-804. Available from: https://doi.org/10.1007/s12559-021-09952-4

Low-level features contain abundant details and high-level features have rich semantic information. Integrating multi-scale features in an appropriate way is significant for salient object detection. However, direct concatenation or addition taken by... Read More about PS-net: progressive selection network for salient object detection..

SAM-Net: semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications. (2021)
Journal Article
YANG, B., XU, X., REN, J., CHENG, L. GUO, L. and ZHANG, Z. 2022. SAM-Net: semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications. Pattern recognition letters [online], 153, pages 126-135. Available from: https://doi.org/10.1016/j.patrec.2021.11.028

3D scene understanding is an essential research topic in the field of Visual Odometry (VO). VO is usually built under the assumption of a static environment, which does not always hold in real scenarios. Existing works fail to consider the dynamic ob... Read More about SAM-Net: semantic probabilistic and attention mechanisms of dynamic objects for self-supervised depth and camera pose estimation in visual odometry applications..

Multi-segment majority voting decision fusion for MI EEG brain-computer interfacing. (2021)
Journal Article
PADFIELD, N., REN, J., QING, C., MURRAY, P., ZHAO, H. and ZHENG, J. 2021. Multi-segment majority voting decision fusion for MI EEG brain-computer interfacing. Cognitive computation [online], 13(6), pages 1484-1495. Available from: https://doi.org/10.1007/s12559-021-09953-3

Brain-computer interfaces (BCIs) based on the electroencephalogram (EEG) generated during motor imagery (MI) have the potential to be used in brain-controlled prosthetics, neurorehabilitation and gaming. Many MI EEG classification systems segment EEG... Read More about Multi-segment majority voting decision fusion for MI EEG brain-computer interfacing..

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..

Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform. (2021)
Journal Article
WANG, J., YANG, M., DING, Z., ZHENG, Q., WANG, D., KPALMA, K. and REN, J. 2021. Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform. Sensors [online], 21(20), article 6720. Available from: https://doi.org/10.3390/s21206720

Variations in the quantity of plankton impact the entire marine ecosystem. It is of great significance to accurately assess the dynamic evolution of the plankton for monitoring the marine environment and global climate change. In this paper, a novel... Read More about Detection of the deep-sea plankton community in marine ecosystem with underwater robotic platform..

MTFFNet: a multi-task feature fusion framework for Chinese painting classification. (2021)
Journal Article
JIANG, W., WANG, X., REN, J., LI, S., SUN, M., WANG, Z. and JIN, J.S. 2021. MTFFNet: a multi-task feature fusion framework for Chinese painting classification. Cognitive computation [online], 13(5), pages 1287-1296. Available from: https://doi.org/10.1007/s12559-021-09896-9

Different artists have their unique painting styles, which can be hardly recognized by ordinary people without professional knowledge. How to intelligently analyze such artistic styles via underlying features remains to be a challenging research prob... Read More about MTFFNet: a multi-task feature fusion framework for Chinese painting classification..

SpaSSA: superpixelwise adaptive SSA for unsupervised spatial-spectral feature extraction in hyperspectral image. (2021)
Journal Article
SUN, G., FU, H., REN, J., ZHANG, A., ZABALZA, J., JIA, X. and ZHAO, H. 2022. SpaSSA: superpixelwise adaptive SSA for unsupervised spatial-spectral feature extraction in hyperspectral image. IEEE transactions on cybernetics [online], 52(7), pages 6158-6169. Available from: https://doi.org/10.1109/TCYB.2021.3104100

Singular spectral analysis (SSA) has recently been successfully applied to feature extraction in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D SSA in spatial domain. However, there are some drawbacks, such as... Read More about SpaSSA: superpixelwise adaptive SSA for unsupervised spatial-spectral feature extraction in hyperspectral image..

Sparse learning of band power features with genetic channel selection for effective classification of EEG signals. (2021)
Journal Article
PADFIELD, N., REN, J., MURRAY, P. and ZHAO, H. 2021. Sparse learning of band power features with genetic channel selection for effective classification of EEG signals. Neurocomputing [online], 463, pages 566-579. Available from: https://doi.org/10.1016/j.neucom.2021.08.067

In this paper, we present a genetic algorithm (GA) based band power feature sparse learning (SL) approach for classification of electroencephalogram (EEG) (GABSLEEG) in motor imagery (MI) based brain-computer interfacing (BCI). The band power in the... Read More about Sparse learning of band power features with genetic channel selection for effective classification of EEG signals..

Spectral-spatial self-attention networks for hyperspectral image classification. (2021)
Journal Article
ZHANG, X., SUN, G., JIA, X., WU, L., ZHANG, A., REN, J., FU, H. and YAO, Y. 2022. Spectral-spatial self-attention networks for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5512115. Available from: https://doi.org/10.1109/TGRS.2021.3102143

This study presents a spectral-spatial self-attention network (SSSAN) for classification of hyperspectral images (HSIs), which can adaptively integrate local features with long-range dependencies related to the pixel to be classified. Specifically, i... Read More about Spectral-spatial self-attention networks for hyperspectral image classification..

A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images. (2021)
Journal Article
FANG, Z., REN, J., MACLELLAN, C., LI, H., ZHOA, H., HUSSAIN, A. and FORTINO, G. 2022. A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images. IEEE transactions on molecular, biological and multi-scale communications [online], 8(1), pages 17-27. Available from: https://doi.org/10.1109/tmbmc.2021.3099367

To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial, chest screening with radiography imaging plays an important role in addition to the real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test. Due... Read More about A novel multi-stage residual feature fusion network for detection of COVID-19 in chest X-ray images..

一种基于模糊成像机理的QR码图像快速盲复原方法. (2021)
Journal Article
CHEN, R., ZHENG, Z., ZHAO, H., REN, J. and TAN, H. 2021. 一种基于模糊成像机理的QR 码图像快速 盲复原方法. = [Fast blind restoration of QR code images based on blurred imaging mechanism]. Guangzi xuebao/Acta photonica sinica [online], 50(7), article 0710003. Available from: https://doi.org/10.3788/gzxb20215007.0710003

A fast blind restoration method of QR code images was proposed based on a blurred imaging mechanism. On the basis of the research on the centroid invariance of the blurred imaging diffuse light spots, the circular finder pattern is designed. When the... Read More about 一种基于模糊成像机理的QR码图像快速盲复原方法..

Fast blind deblurring of QR code images based on adaptive scale control. (2021)
Journal Article
CHEN, R., ZHENG, Z., PAN, J., YU, Y., ZHAO, H. and REN, J. 2022. Fast blind deblurring of QR code images based on adaptive scale control. Mobile networks and applications [online], 26(6), pages 2472-2487. Available from: https://doi.org/10.1007/s11036-021-01780-y

With the development of 5G technology, the short delay requirements of commercialization and large amounts of data change our lifestyle day-to-day. In this background, this paper proposes a fast blind deblurring algorithm for QR code images, which ma... Read More about Fast blind deblurring of QR code images based on adaptive scale control..