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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..

A lightweight deep learning-based approach for concrete crack characterization using acoustic emission signals. (2021)
Journal Article
HABIB, M.A., HASAN, M.J. and KIM, J.-M. 2021. A lightweight deep learning-based approach for concrete crack characterization using acoustic emission signals. IEEE access [online], 9, pages 104029-104050. Available from: https://doi.org/10.1109/ACCESS.2021.3099124

This paper proposes an acoustic emission (AE) based automated crack characterization method for reinforced concrete (RC) beams using a memory efficient lightweight convolutional neural network named SqueezeNet. The proposed method also includes a sig... Read More about A lightweight deep learning-based approach for concrete crack characterization using acoustic emission signals..

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..

SLSNet: skin lesion segmentation using a lightweight generative adversarial network. (2021)
Journal Article
SARKER, M.M.K., RASHWAN, H.A., AKRAM, F., SINGH, V.K., BANU, S.F., CHOWDHURY, F.U.H., CHOUDHURY, K.A., CHAMBON, S., RADEVA, P., PUIG, D. and ABDEL-NASSER, M. 2021. SLSNet: skin lesion segmentation using a lightweight generative adversarial network. Expert systems with applications [online], 183, article 115433. Available from: https://doi.org/10.1016/j.eswa.2021.115433

The determination of precise skin lesion boundaries in dermoscopic images using automated methods faces many challenges, most importantly, the presence of hair, inconspicuous lesion edges and low contrast in dermoscopic images, and variability in the... Read More about SLSNet: skin lesion segmentation using a lightweight generative adversarial network..

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..

An explainable AI-based fault diagnosis model for bearings. (2021)
Journal Article
HASAN, M.J., SOHAIB, M. and KIM, J.-M. 2021. An explainable AI-based fault diagnosis model for bearings. Sensors [online], 21(12): sensing technologies for fault diagnostics and prognosis, article 4070. Available from: https://doi.org/10.3390/s21124070

In this paper, an explainable AI-based fault diagnosis model for bearings is proposed with five stages, i.e., (1) a data preprocessing method based on the Stockwell Transformation Coefficient (STC) is proposed to analyze the vibration signals for var... Read More about An explainable AI-based fault diagnosis model for bearings..

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..

KonVid-150k: a dataset for no-reference video quality assessment of videos in-the-wild. (2021)
Journal Article
GÖTZ-HAHN, F., HOSU, V., LIN, H. and SAUPE, D. 2021. KonVid-150k: a dataset for no-reference video quality assessment of videos in-the-wild. IEEE access [online], 9, pages 72139-72160. Available from: https://doi.org/10.1109/access.2021.3077642

Video quality assessment (VQA) methods focus on particular degradation types, usually artificially induced on a small set of reference videos. Hence, most traditional VQA methods under-perform in-the-wild. Deep learning approaches have had limited su... Read More about KonVid-150k: a dataset for no-reference video quality assessment of videos in-the-wild..

Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter. (2021)
Journal Article
ZHU, H., CHEN, W., ZHU, R., ZHANG, L., FU, B. and LU, X. 2021. Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter. Proceedings of the Institution of Mechanical Engineers, part C: journal of mechanical engineering science [online], 235(22), pages 5975-5993. Available from: https://doi.org/10.1177/0954406221992798

The coupled dynamic model of the intermediate and tail gearboxes’ spiral bevel gear-oblique tail shaft-laminated membrane coupling was established by employing the hybrid modeling method of finite element and lumped mass. Among them, the dynamic equa... Read More about Modeling and dynamic analysis of spiral bevel gear coupled system of intermediate and tail gearboxes in a helicopter..

Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. (2021)
Journal Article
ZHANG, L., LIM, C.P. and YU, Y. 2021. Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization. Knowledge-based systems [online], 220, article ID 106918. Available from: https://doi.org/10.1016/j.knosys.2021.106918

Automatic interpretation of human actions from realistic videos attracts increasing research attention owing to its growing demand in real-world deployments such as biometrics, intelligent robotics, and surveillance. In this research, we propose an e... Read More about Intelligent human action recognition using an ensemble model of evolving deep networks with swarm-based optimization..

Feature selection using enhanced particle swarm optimisation for classification models. (2021)
Journal Article
XIE, H., ZHANG, L., LIM, C.P., YU, Y. and LIU, H. 2021. Feature selection using enhanced particle swarm optimisation for classification models. Sensors [online], 21(5), article 1816. Available from: https://doi.org/10.3390/s21051816

In this research, we propose two Particle Swarm Optimisation (PSO) variants to undertake feature selection tasks. The aim is to overcome two major shortcomings of the original PSO model, i.e., premature convergence and weak exploitation around the ne... Read More about Feature selection using enhanced particle swarm optimisation for classification models..

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..

Particle swarm optimization for automatically evolving convolutional neural networks for image classification. (2021)
Journal Article
LAWRENCE, T., ZHANG, L., LIM, C.P. and PHILLIPS, E.-J. 2021. Particle swarm optimization for automatically evolving convolutional neural networks for image classification. IEEE access [online], 9, pages 14369-14386. Available from: https://doi.org/10.1109/ACCESS.2021.3052489

Designing Convolutional Neural Networks from scratch is a time-consuming process that requires specialist expertise. While automated architecture generation algorithms have been proposed, the underlying search strategies generally are computationally... Read More about Particle swarm optimization for automatically evolving convolutional neural networks for image classification..

A multitask-aided transfer learning-based diagnostic framework for bearings under inconsistent working conditions. (2020)
Journal Article
HASAN, M.J., SOHAIB, M. and KIM, J.-M. 2020. A multitask-aided transfer learning-based diagnostic framework for bearings under inconsistent working conditions. Sensors [online], 20(24): deep learning, artificial neural networks and sensors for fault diagnosis, article 7205. Available from: https://doi.org/10.3390/s20247205

Rolling element bearings are a vital part of rotating machines and their sudden failure can result in huge economic losses as well as physical causalities. Popular bearing fault diagnosis techniques include statistical feature analysis of time, frequ... Read More about A multitask-aided transfer learning-based diagnostic framework for bearings under inconsistent working conditions..

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..

Rotate vector (Rv) reducer fault detection and diagnosis system: towards component level prognostics and health management (phm). (2020)
Journal Article
ROHAN, A., RAOUF, I. and KIM, H.S. 2020. Rotate vector (Rv) reducer fault detection and diagnosis system: towards component level prognostics and health management (phm). Sensors [online], 20(23), article 6845. Available from: https://doi.org/10.3390/s20236845

In prognostics and health management (PHM), the majority of fault detection and diagnosis is performed by adopting segregated methodology, where electrical faults are detected using motor current signature analysis (MCSA), while mechanical faults are... Read More about Rotate vector (Rv) reducer fault detection and diagnosis system: towards component level prognostics and health management (phm)..