All Outputs (138)

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..

Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing. (2021)
Journal Article
CHEN, R., ZHENG, Z., YU, Y., ZHAO, H., REN, J. and TAN, H.-Z. 2021. Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing. IEEE sensors journal [online], 21(16), article 103048, pages 18222-18236. Available from: https://doi.org/10.1109/JSEN.2021.3085568

Out-of-focus blurring of the QR code is very common in mobile Internet systems, which often causes failure of authentication as a result of a misreading of the information hence adversely affects the operation of the system. To tackle this difficulty... Read More about Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing..

Novel gumbel-softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection. (2021)
Journal Article
SUN, H., REN, J., ZHAO, H., YUEN, P. and TSCHANNERL, J. 2022. Novel gumbel-softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection. IEEE transactions on geoscience and remote sensing [online], 60, article 5506413. Available from: https://doi.org/10.1109/TGRS.2021.3075663

As an important topic in hyperspectral image (HSI) analysis, band selection has attracted increasing attention in the last two decades for dimensionality reduction in HSI. With the great success of deep learning (DL)-based models recently, a robust u... Read More about Novel gumbel-softmax trick enabled concrete autoencoder with entropy constraints for unsupervised hyperspectral band selection..

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..

Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets. (2021)
Journal Article
SUN, H., LIU, Q., WANG, J., REN, J., WU, Y., ZHAO, H. and LI, H. 2021. Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 2971-2983. Available from: https://doi.org/10.1109/JSTARS.2021.3061496

Detection of the low-altitude and slow-speed small (LSS) targets is one of the most popular research topics in remote sensing. Despite of a few existing approaches, there is still an accuracy gap for satisfying the practical needs. As the LSS targets... Read More about Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets..

A new cost function for spatial image steganography based on 2D-SSA and WMF. (2021)
Journal Article
XIE, G., REN, J., MARSHALL, S., ZHAO, H. and LI, H. 2021. A new cost function for spatial image steganography based on 2D-SSA and WMF. IEEE access [online], 9, pages 30604-30614. Available from: https://doi.org/10.1109/ACCESS.2021.3059690

As an essential tool for secure communications, adaptive steganography aims to communicate secret information with the least security cost. Inspired by the Ranking Priority Profile (RPP), we propose a novel two-step cost function for adaptive stegano... Read More about A new cost function for spatial image steganography based on 2D-SSA and WMF..

A framework for breast cancer classification using multi-DCNNs. (2021)
Journal Article
RAGAB, D.A., ATTALLAH, O., SHARKAS, M., REN, J. and MARSHALL, S. 2021. A framework for breast cancer classification using multi-DCNNs. Computers in biology and medicine [online], 131, article number 104245. Available from: https://doi.org/10.1016/j.compbiomed.2021.104245

Deep learning (DL) is the fastest-growing field of machine learning (ML). Deep convolutional neural networks (DCNN) are currently the main tool used for image analysis and classification purposes. There are several DCNN architectures among them AlexN... Read More about A framework for breast cancer classification using multi-DCNNs..

EACOFT: an energy-aware correlation filter for visual tracking. (2020)
Journal Article
LIU, Q., REN, J., WANG, Y., WU, Y., SUN, H. and ZHAO, H. 2021. EACOFT: an energy-aware correlation filter for visual tracking. Pattern recognition [online], 112, article ID 107766. Available from: https://doi.org/10.1016/j.patcog.2020.107766

Correlation filter based trackers attribute to its calculation in the frequency domain can efficiently locate targets in a relatively fast speed. This characteristic however also limits its generalization in some specific scenarios. The reasons that... Read More about EACOFT: an energy-aware correlation filter for visual tracking..

DRL-GAN: dual-stream representation learning GAN for low-resolution image classification in UAV applications. (2020)
Journal Article
XI, Y., JIA, W., ZHENG, J., FAN, X., XIE, Y., REN, J. and HE, X. 2021. DRL-GAN: dual-stream representation learning GAN for low-resolution image classification in UAV applications. IEEE Journal of selected topics in applied earth observations and remote sensing [online], 14, pages 1705-1716. Available from: https://doi.org/10.1109/JSTARS.2020.3043109

Identifying tiny objects from extremely low resolution (LR) UAV-based remote sensing images is generally considered as a very challenging task, because of very limited information in the object areas. In recent years, there have been very limited att... Read More about DRL-GAN: dual-stream representation learning GAN for low-resolution image classification in UAV applications..

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..

Multiscale 2-D singular spectrum analysis and principal component analysis for spatial–spectral noise-robust feature extraction and classification of hyperspectral images. (2020)
Journal Article
MA, P., REN, J., ZHAO, H., SUN, G., MURRAY, P. and ZHENG, J. 2021. Multiscale 2-D singular spectrum analysis and principal component analysis for spatial–spectral noise-robust feature extraction and classification of hyperspectral images. IEEE journal of selected topics in applied earth observations and remote sensing [online], 14, pages 1233-1245. Available from: https://doi.org/10.1109/JSTARS.2020.3040699

In hyperspectral images (HSI), most feature extraction and data classification methods rely on corrected dataset, in which the noisy and water absorption bands are removed. This can result in not only extra working burden but also information loss fr... Read More about Multiscale 2-D singular spectrum analysis and principal component analysis for spatial–spectral noise-robust feature extraction and classification of hyperspectral images..

Fusion of PCA and segmented-PCA domain multiscale 2-D-SSA for effective spectral-spatial feature extraction and data classification in hyperspectral imagery. (2020)
Journal Article
FU, H., SUN, G., REN, J., ZHANG, A. and JIA, X. 2020. Fusion of PCA and segmented-PCA domain multiscale 2-D-SSA for effective spectral-spatial feature extraction and data classification in hyperspectral imagery. IEEE transactions on geoscience and remote sensing [online], 60, article 5500214. Available from: https://doi.org/10.1109/TGRS.2020.3034656

As hyperspectral imagery (HSI) contains rich spectral and spatial information, a novel principal component analysis (PCA) and segmented-PCA (SPCA)-based multiscale 2-D-singular spectrum analysis (2-D-SSA) fusion method is proposed for joint spectral–... Read More about Fusion of PCA and segmented-PCA domain multiscale 2-D-SSA for effective spectral-spatial feature extraction and data classification in hyperspectral imagery..

Iterative enhanced multivariance products representation for effective compression of hyperspectral images. (2020)
Journal Article
TUNA, S., TÖREYIN, B.U., REN, J., ZHAO, H. and MARSHALL, S. 2021. Iterative enhanced multivariance products representation for effective compression of hyperspectral images. IEEE transactions on geoscience and remote sensing [online], 59(11), pages 9569-9584. Available from: https://doi.org/10.1109/TGRS.2020.3031016

Effective compression of hyperspectral (HS) images is essential due to their large data volume. Since these images are high dimensional, processing them is also another challenging issue. In this work, an efficient lossy HS image compression method b... Read More about Iterative enhanced multivariance products representation for effective compression of hyperspectral images..

Text to realistic image generation with attentional concatenation generative adversarial networks. (2020)
Journal Article
LI, L., SUN, Y., HU, F., ZHOU, T., XI, X. and REN, J. 2020. Text to realistic image generation with attentional concatenation generative adversarial networks. Discrete dynamics in nature and society [online], 2020, article ID 6452536. Available from: https://doi.org/10.1155/2020/6452536

In this paper, we propose an Attentional Concatenation Generative Adversarial Network (ACGAN) aiming at generating 1024 × 1024 high-resolution images. First, we propose a multilevel cascade structure, for text-to-image synthesis. During training prog... Read More about Text to realistic image generation with attentional concatenation generative adversarial networks..

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..

Effective melanoma recognition using deep convolutional neural network with covariance discriminant loss. (2020)
Journal Article
GUO, L., XIE, G., XU, X. and REN, J. 2020. Effective melanoma recognition using deep convolutional neural network with covariance discriminant loss. Sensors [online], 20(20), article 5786. Available from: https://doi.org/10.3390/s20205786

Melanoma recognition is challenging due to data imbalance and high intra-class variations and large inter-class similarity. Aiming at the issues, we propose a melanoma recognition method using deep convolutional neural network with covariance discrim... Read More about Effective melanoma recognition using deep convolutional neural network with covariance discriminant loss..

SAFDet: a semi-anchor-free detector for effective detection of oriented objects in aerial images. (2020)
Journal Article
FANG, Z., REN, J., SUN, H., MARSHALL, S., HAN, J. and ZHAO, H. 2020. SAFDet: a semi-anchor-free detector for effective detection of oriented objects in aerial images. Remote sensing [online], 12(19), article 3225. Available from: https://doi.org/10.3390/rs12193225

An oriented bounding box (OBB) is preferable over a horizontal bounding box (HBB) in accurate object detection. Most of existing works utilize a two-stage detector for locating the HBB and OBB, respectively, which have suffered from the misaligned ho... Read More about SAFDet: a semi-anchor-free detector for effective detection of oriented objects in aerial images..

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..

Rewritable and sustainable 2D barcode for traceability application in smart IoT based fault-tolerant mechanism. (2020)
Journal Article
CHEN, R., YU, Y., XIE, S., ZHAO, H., LIU, S., REN, J. and TAN, H.-Z. 2020. Rewritable and sustainable 2D barcode for traceability application in smart IoT based fault-tolerant mechanism. Sustainability [online], 12(17), article 7192. Available from: https://doi.org/10.3390/su12177192

With the development of the Internet of Things (IoT) technology, two-dimensional (2D) barcodes are widely used in smart IoT applications as a perception portal. In industries with many circulations and testing links like traceability, since the exist... Read More about Rewritable and sustainable 2D barcode for traceability application in smart IoT based fault-tolerant mechanism..

Topological optimization of the DenseNet with pretrained-weights inheritance and genetic channel selection. (2020)
Journal Article
FANG, Z, REN, J., MARSHALL, S., ZHAO, H., WANG, S. and LI, X. 2021. Topological optimization of the DenseNet with pretrained-weights inheritance and genetic channel selection. Pattern recognition [online], 109, article ID 107608. Available from: https://doi.org/10.1016/j.patcog.2020.107608

Convolutional neural networks (CNNs) have been successfully applied in many computer vision applications, especially in image classification tasks, where most of the structures have been designed manually. With the aid of skip connection and dense co... Read More about Topological optimization of the DenseNet with pretrained-weights inheritance and genetic channel selection..