All Outputs (115)

A novel band selection and spatial noise reduction method for hyperspectral image classification. (2022)
Journal Article
FU, H., ZHANG, A., SUN, G., REN, J., JIA, X., PAN, Z. and MA, H. 2022. A novel band selection and spatial noise reduction method for hyperspectral image classification. IEEE transactions on geoscience and remote sensing [online], 60, article 5535713. Available from: https://doi.org/10.1109/TGRS.2022.3189015

As an essential reprocessing method, dimensionality reduction (DR) can reduce the data redundancy and improve the performance of hyperspectral image (HSI) classification. A novel unsupervised DR framework with feature interpretability, which integrat... Read More about A novel band selection and spatial noise reduction method for hyperspectral image classification..

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..

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..

Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation. (2022)
Conference Proceeding
CHEN, S., YAN, Y., REN, J., HWANG, B., MARSHALL, S. and DARRANI, T. 2022. Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 1004-1012. Available from: https://doi.org/10.1007/978-981-19-0390-8_126

By grouping pixels with visual coherence, superpixel algorithms provide an alternative representation of regular pixel grid for precise and efficient image segmentation. In this paper, a multi-stage model is used for sea ice segmentation from the hig... Read More about Superpixel based sea ice segmentation with high-resolution optical images: analysis and evaluation..

Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. (2022)
Conference Proceeding
YAN, Y., ZHANG, Y., REN, J., HADJAL, M., MCKEE, D., KAO, F.-J., and DURRANI, T. 2022. Estimation of chlorophyll concentration for environment monitoring in Scottish marine water. In Liang, Q., Wang, W., Liu, X., Na, Z. and Zhang, B. (eds.) Communications, signal processing and systems: proceedings of the 10th International conference on Communications, signal processing and systems 2021 (CSPS 2021), 21-22 August 2021, Baishishan, China. Lecture notes in electrical engineering, 878. Singapore: Springer [online], 1, pages 582-587. Available from: https://doi.org/10.1007/978-981-19-0390-8_71

Marine Scotland is tasked with reporting on the environmental status of Scottish marine waters, an enormous area of water extending from the shoreline to deep oceanic waters. As one of the most important variables, chlorophyll concentration (Chl) pla... Read More about Estimation of chlorophyll concentration for environment monitoring in Scottish marine water..

MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset] (2022)
Dataset
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. [Dataset]. Hosted on GitHub [online]. Available from: https://github.com/Lm0324/MVVA-Net

Most of the existing video aesthetic quality assessment datasets (as seen in Table 1) are not public, some are not large enough, which makes the trained depth model perform poorly and some are based on the professionalism of video shooting or the rat... Read More about MVVA-net: a video aesthetic quality assessment network with cognitive fusion of multi-type feature–based strong generalization. [Dataset].

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..

Folded LDA: extending the linear discriminant analysis algorithm for feature extraction and data reduction in hyperspectral remote sensing. (2021)
Journal Article
FABIYI, S.D., MURRAY, P., ZABALZA, J. and REN, J. 2021. Folded LDA: extending the linear discriminant analysis algorithm for feature extraction and data reduction in hyperspectral remote sensing. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 12312-12331. Available from: https://doi.org/10.1109/JSTARS.2021.3129818

The rich spectral information provided by hyperspectral imaging (HSI) has made this technology very useful in the classification of remotely sensed data. However, classification of hyperspectral data is typically affected by noise and the Hughes phen... Read More about Folded LDA: extending the linear discriminant analysis algorithm for feature extraction and data reduction in hyperspectral remote sensing..

Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-net. (2021)
Journal Article
REN, J., SUN, H., ZHAO, H., GAO, H., MACLELLAN, C., ZHAO, S. and LUO, X. 2022. Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-net. Pattern recognition letters [online], 155, pages 165-170. Available from: https://doi.org/10.1016/j.patrec.2021.10.025

Accurate extraction of semantic objects such as ventricles and myocardium from magnetic resonance (MR) images is one essential but very challenging task for the diagnosis of the cardiac diseases. To tackle this problem, in this paper, an automatic en... Read More about Effective extraction of ventricles and myocardium objects from cardiac magnetic resonance images with a multi-task learning U-net..

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..