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A 3-DOF piezoelectric driven nanopositioner: Design, control and experiment (2021)
Journal Article
Li, P., Zhang, D., Lennox, B., & Arvin, F. (2021). A 3-DOF piezoelectric driven nanopositioner: Design, control and experiment. Mechanical Systems and Signal Processing, 155, Article 107603. https://doi.org/10.1016/j.ymssp.2020.107603

In this paper, a novel 3-degree-of-freedom (DOF) nanopositioner was investigated in order to position objects with nanometer scale accuracy. Nanopositioners are used in a variety of real-world applications, e.g. biomedical technology and nanoassembly... Read More about A 3-DOF piezoelectric driven nanopositioner: Design, control and experiment.

Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection (2021)
Journal Article
Bera, A., Bhattacharjee, D., & Shum, H. P. (2021). Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection. Expert Systems with Applications, 171, https://doi.org/10.1016/j.eswa.2021.114583

This paper presents a human verification scheme in two independent stages to overcome the vulnerabilities of attacks and to enhance security. At the first stage, a hand image-based CAPTCHA (HandCAPTCHA) is tested to avert automated bot-attacks on the... Read More about Two-stage human verification using HandCAPTCHA and anti-spoofed finger biometrics with feature selection.

Multi-task Deep Learning with Optical Flow Features for Self-Driving Cars (2020)
Journal Article
Hu, Y., Shum, H. P., & Ho, E. S. (2020). Multi-task Deep Learning with Optical Flow Features for Self-Driving Cars. IET Intelligent Transport Systems, 14(13), 1845-1854. https://doi.org/10.1049/iet-its.2020.0439

The control of self-driving cars has received growing attention recently. Although existing research shows promising results in the vehicle control using video from a monocular dash camera, there has been very limited work on directly learning vehicl... Read More about Multi-task Deep Learning with Optical Flow Features for Self-Driving Cars.

A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications (2020)
Journal Article
Bhattacharya, M., Roy, S., Mistry, K., Shum, H. P., & Chattopadhyay, S. (2020). A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications. IEEE Access, 8, https://doi.org/10.1109/access.2020.3043621

The rapid development of mobile internet technology and the better availability of GPS have made mobile online social networks (mOSNs) more popular than traditional online social networks (OSNs) over the last few years. They necessitate fundamental s... Read More about A Privacy-Preserving Efficient Location-Sharing Scheme for Mobile Online Social Network Applications.

A plug-in attribute correction module for generalized zero-shot learning (2020)
Journal Article
Zhang, H., Bai, H., Long, Y., Liu, L., & Shao, L. (2021). A plug-in attribute correction module for generalized zero-shot learning. Pattern Recognition, 112, Article 107767. https://doi.org/10.1016/j.patcog.2020.107767

While Zero Shot Learning models can recognize new classes without training examples, they often fails to incorporate both seen and unseen classes together at the test time, which is known as the Generalized Zero-shot Learning (GZSL) problem. This pap... Read More about A plug-in attribute correction module for generalized zero-shot learning.

Modality independent adversarial network for generalized zero shot image classification (2020)
Journal Article
Zhang, H., Wang, Y., Long, Y., Yang, L., & Shao, L. (2021). Modality independent adversarial network for generalized zero shot image classification. Neural Networks, 134, 11-22. https://doi.org/10.1016/j.neunet.2020.11.007

Zero Shot Learning (ZSL) aims to classify images of unseen target classes by transferring knowledge from source classes through semantic embeddings. The core of ZSL research is to embed both visual representation of object instance and semantic descr... Read More about Modality independent adversarial network for generalized zero shot image classification.

A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction (2020)
Journal Article
Men, Q., Ho, E. S., Shum, H. P., & Leung, H. (2021). A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction. IEEE Transactions on Circuits and Systems for Video Technology, 31(9), 3417-3432. https://doi.org/10.1109/tcsvt.2020.3038145

Recurrent neural network (RNN) has become popular for human motion prediction thanks to its ability to capture temporal dependencies. However, it has limited capacity in modeling the complex spatial relationship in the human skeletal structure. In th... Read More about A Quadruple Diffusion Convolutional Recurrent Network for Human Motion Prediction.

Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning (2020)
Journal Article
Hu, J., Niu, H., Carrasco, J., Lennox, B., & Arvin, F. (2020). Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology, 69(12), https://doi.org/10.1109/tvt.2020.3034800

Autonomous exploration is an important application of multi-vehicle systems, where a team of networked robots are coordinated to explore an unknown environment collaboratively. This technique has earned significant research interest due to its useful... Read More about Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning.

Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models (2020)
Book Chapter
Gajbhiye, A., Winterbottom, T., Al Moubayed, N., & Bradley, S. (2020). Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models. In I. Farkaš, P. Masulli, & S. Wermter (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2020 (633-646). Springer Verlag. https://doi.org/10.1007/978-3-030-61609-0_50

We consider the task of incorporating real-world commonsense knowledge into deep Natural Language Inference (NLI) models. Existing external knowledge incorporation methods are limited to lexical-level knowledge and lack generalization across NLI mode... Read More about Bilinear Fusion of Commonsense Knowledge with Attention-Based NLI Models.

Facial reshaping operator for controllable face beautification (2020)
Journal Article
Hu, S., Shum, H. P., Liang, X., Li, F. W., & Aslam, N. (2021). Facial reshaping operator for controllable face beautification. Expert Systems with Applications, 167, Article 114067. https://doi.org/10.1016/j.eswa.2020.114067

Posting attractive facial photos is part of everyday life in the social media era. Motivated by the demand, we propose a lightweight method to automatically and efficiently beautify the shapes of both portrait and non-portrait faces in photos, while... Read More about Facial reshaping operator for controllable face beautification.

On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery (2020)
Presentation / Conference Contribution
Wang, Q., Bhowmik, N., & Breckon, T. (2020). On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery. In Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN) (1-8). https://doi.org/10.1109/ijcnn48605.2020.9207389

X-ray Computed Tomography (CT) based 3D imaging is widely used in airports for aviation security screening whilst prior work on prohibited item detection focuses primarily on 2D X-ray imagery. In this paper, we aim to evaluate the possibility of exte... Read More about On the Evaluation of Prohibited Item Classification and Detection in Volumetric 3D Computed Tomography Baggage Security Screening Imagery.

Visible to Infrared Transfer Learning as a Paradigm for Accessible Real-time Object Detection and Classification in Infrared Imagery (2020)
Presentation / Conference Contribution
Gaus, Y., Bhowmik, N., Isaac-Medina, B., & Breckon, T. (2020). Visible to Infrared Transfer Learning as a Paradigm for Accessible Real-time Object Detection and Classification in Infrared Imagery. In H. Bouma, R. Prabhu, R. J. Stokes, & Y. Yitzhaky (Eds.), Proceedings volume 11542, counterterrorism, crime fighting, forensics, and surveillance technologies IV. https://doi.org/10.1117/12.2573968

Object detection from infrared-band (thermal) imagery has been a challenging problem for many years. With the advent of deep Convolutional Neural Networks (CNN), the automated detection and classification of objects of interest within the scene has b... Read More about Visible to Infrared Transfer Learning as a Paradigm for Accessible Real-time Object Detection and Classification in Infrared Imagery.

Target‐driven cloud evolution using position‐based fluids (2020)
Journal Article
Zhang, Z., Li, Y., Yang, B., Li, F. W., & Liang, X. (2020). Target‐driven cloud evolution using position‐based fluids. Computer Animation and Virtual Worlds, 31(6), https://doi.org/10.1002/cav.1937

To effectively control particle‐based cloud evolution without imposing strict position constraints, we propose a novel method integrating a control force field and a phase transition control into the position‐based fluids (PBF) framework. To produce... Read More about Target‐driven cloud evolution using position‐based fluids.

Swarm Intelligence and cyber-physical systems: Concepts, challenges and future trends (2020)
Journal Article
Schranz, M., Di Caro, G. A., Schmickl, T., Elmenreich, W., Arvin, F., Şekercioğlu, A., & Sende, M. (2021). Swarm Intelligence and cyber-physical systems: Concepts, challenges and future trends. Swarm and Evolutionary Computation, 60, Article 100762. https://doi.org/10.1016/j.swevo.2020.100762

Swarm Intelligence (SI) is a popular multi-agent framework that has been originally inspired by swarm behaviors observed in natural systems, such as ant and bee colonies. In a system designed after swarm intelligence, each agent acts autonomously, re... Read More about Swarm Intelligence and cyber-physical systems: Concepts, challenges and future trends.