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All Outputs (120)

Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention (2021)
Conference Proceeding
Organisciak, D., Ho, E. S., & Shum, H. P. (2021). Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention. . https://doi.org/10.1109/icpr48806.2021.9412604

Facial makeup style transfer is an extremely challenging sub-field of image-to-image-translation. Due to this difficulty, state-of-the-art results are mostly reliant on the Face Parsing Algorithm, which segments a face into parts in order to easily e... Read More about Makeup Style Transfer on Low-quality Images with Weighted Multi-scale Attention.

Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery (2021)
Conference Proceeding
Sasaki, H., Willcocks, C., & Breckon, T. (2021). Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery. . https://doi.org/10.1109/icpr48806.2021.9413023

Machine learning driven object detection and classification within non-visible imagery has an important role in many fields such as night vision, all-weather surveillance and aviation security. However, such applications often suffer due to the limit... Read More about Data Augmentation via Mixed Class Interpolation using Cycle-Consistent Generative Adversarial Networks Applied to Cross-Domain Imagery.

Real Time Fencing Move Classification and Detection at Touch Time during a Fencing Match (2021)
Conference Proceeding
Sunal, C. E., Willcocks, C. G., & Obara, B. (2021). Real Time Fencing Move Classification and Detection at Touch Time during a Fencing Match. . https://doi.org/10.1109/icpr48806.2021.9412024

Fencingis a fast-paced sport played with swords which are Épée, Foil, and Sabre. However, such fast-pace can cause referees to make wrong decisions. Review of slow-motion camera footage in tournaments helps referees' decision-making, but it interrupt... Read More about Real Time Fencing Move Classification and Detection at Touch Time during a Fencing Match.

Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI (2021)
Conference Proceeding
Aznan, N., Atapour-Abarghouei, A., Bonner, S., Connolly, J., & Breckon, T. (2021). Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI. . https://doi.org/10.1109/icpr48806.2021.9411994

Recently, substantial progress has been made in the area of Brain-Computer Interface (BCI) using modern machine learning techniques to decode and interpret brain signals. While Electroencephalography (EEG) has provided a non-invasive method of interf... Read More about Leveraging Synthetic Subject Invariant EEG Signals for Zero Calibration BCI.

Improving Robotic Grasping on Monocular Images Via Multi-Task Learning and Positional Loss (2021)
Conference Proceeding
Prew, W., Breckon, T., Bordewich, M., & Beierholm, U. (2021). Improving Robotic Grasping on Monocular Images Via Multi-Task Learning and Positional Loss. . https://doi.org/10.1109/icpr48806.2021.9413197

In this paper we introduce two methods of improving real-time object grasping performance from monocular colour images in an end-to-end CNN architecture. The first is the addition of an auxiliary task during model training (multi-task learning). Our... Read More about Improving Robotic Grasping on Monocular Images Via Multi-Task Learning and Positional Loss.

Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning (2021)
Conference Proceeding
Watson, M., & Al Moubayed, N. (2021). Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning. . https://doi.org/10.1109/icpr48806.2021.9412560

Explainable machine learning has become increasingly prevalent, especially in healthcare where explainable models are vital for ethical and trusted automated decision making. Work on the susceptibility of deep learning models to adversarial attacks h... Read More about Attack-agnostic Adversarial Detection on Medical Data Using Explainable Machine Learning.

On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures (2021)
Conference Proceeding
Poyser, M., Atapour-Abarghouei, A., & Breckon, T. (2021). On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures. . https://doi.org/10.1109/icpr48806.2021.9412455

Recent advances in generalized image understanding have seen a surge in the use of deep convolutional neural networks (CNN) across a broad range of image-based detection, classification and prediction tasks. Whilst the reported performance of these a... Read More about On the Impact of Lossy Image and Video Compression on the Performance of Deep Convolutional Neural Network Architectures.

A Two-Stream Recurrent Network for Skeleton-based Human Interaction Recognition (2021)
Conference Proceeding
Men, Q., Hoy, E. S., Shum, H. P., & Leung, H. (2021). A Two-Stream Recurrent Network for Skeleton-based Human Interaction Recognition. . https://doi.org/10.1109/icpr48806.2021.9412538

This paper addresses the problem of recognizing human-human interaction from skeletal sequences. Existing methods are mainly designed to classify single human action. Many of them simply stack the movement features of two characters to deal with huma... Read More about A Two-Stream Recurrent Network for Skeleton-based Human Interaction Recognition.

Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery (2021)
Conference Proceeding
Isaac-Medina, B., Willcocks, C., & Breckon, T. (2021). Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery. . https://doi.org/10.1109/icpr48806.2021.9413007

Automatic detection for threat object items is an increasing emerging area of future application in X-ray security imagery. Although modern X-ray security scanners can provide two or more views, the integration of such object detectors across the vie... Read More about Multi-view Object Detection Using Epipolar Constraints within Cluttered X-ray Security Imagery.

Colouring graphs of bounded diameter in the absence of small cycles (2021)
Conference Proceeding
Martin, B., Paulusma, D., & Smith, S. (2021). Colouring graphs of bounded diameter in the absence of small cycles. In T. Calamoneri, & F. Corò (Eds.), . https://doi.org/10.1007/978-3-030-75242-2_26

For k ≥ 1, a k-colouring c of G is a mapping from V (G) to {1, 2, . . . , k} such that c(u) 6= c(v) for any two non-adjacent vertices u and v. The k-Colouring problem is to decide if a graph G has a k-colouring. For a family of graphs H, a graph G is... Read More about Colouring graphs of bounded diameter in the absence of small cycles.

Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners (2021)
Conference Proceeding
Pereira, F. D., Oliveira, E. H. T. D., Oliveira, D. B. F. D., Carvalho, L. S. G. D., & Cristea, A. I. (2021). Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners. . https://doi.org/10.5753/educomp_estendido.2021.14853

Building predictive models to estimate the learner performance in the beginning of CS1 courses is essential in education to allow early interventions. However, the educational literature notes the lack of studies on early learner behaviours that can... Read More about Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners.

COVID-19’s Impact on the Telecommunications Companies (2021)
Conference Proceeding
Almuqren, L., & Cristea, A. I. (2021). COVID-19’s Impact on the Telecommunications Companies. In Á. Rocha, H. Adeli, G. Dzemyda, F. Moreira, & A. M. R. Correia (Eds.), WorldCIST 2021: Trends and Applications in Information Systems and Technologies (318-327). https://doi.org/10.1007/978-3-030-72654-6_31

Now the world is witnessing most significant challenges due the Covid-19 crisis. Beyond health effects, it has social and economic effects. With the enormous amount of data available and the widespread use of social web globally, research can and sho... Read More about COVID-19’s Impact on the Telecommunications Companies.

A Seamless and Efficient Transition Algorithm For Aerial Drone Multicasting (2021)
Conference Proceeding
Tu, W. (2021). A Seamless and Efficient Transition Algorithm For Aerial Drone Multicasting. In CCNC 2021: 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC) (1-6). https://doi.org/10.1109/ccnc49032.2021.9369559

Drone communications make use of line-of-sight coverage of drones to realise services that ground devices may not support. Many relevant applications such as video capture by drones and drone traffic management, require group communications between d... Read More about A Seamless and Efficient Transition Algorithm For Aerial Drone Multicasting.

Towards a Human-AI hybrid system for categorising programming problems (2021)
Conference Proceeding
Pereira, F. D., Piris, F., Cristo da Fonseca, S., Cristea, A., Oliveira, E. H., Carvalho, L., & Fernandes, D. (2021). Towards a Human-AI hybrid system for categorising programming problems. In SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (94-100). https://doi.org/10.1145/3408877.3432422

As programming skills are increasingly required world-wide and across disciplines, many students use online platforms that provide automatic feedback through a Programming Online Judge (POJ) mechanism. POJs are very popular e-learning tools, boasting... Read More about Towards a Human-AI hybrid system for categorising programming problems.

Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery (2021)
Conference Proceeding
Wang, Q., Bhowmik, N., & Breckon, T. (2021). Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery. . https://doi.org/10.1109/icmla51294.2020.00012

Automatic detection of prohibited objects within passenger baggage is important for aviation security. X-ray Computed Tomography (CT) based 3D imaging is widely used in airports for aviation security screening whilst prior work on automatic prohibite... Read More about Multi-Class 3D Object Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery.

Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection (2021)
Conference Proceeding
Thomson, W., Bhowmik, N., & Breckon, T. (2021). Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection. . https://doi.org/10.1109/icmla51294.2020.00030

Automatic visual fire detection is used to complement traditional fire detection sensor systems (smoke/heat). In this work, we investigate different Convolutional Neural Network (CNN) architectures and their variants for the non-temporal real-time bo... Read More about Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire Detection.

Student Perceptions of Assessment and Feedback - are they valid? (2021)
Conference Proceeding
Crosby, R. (2021). Student Perceptions of Assessment and Feedback - are they valid?. In CEP '21: Proceedings of the 5th Conference on Computing Education Practice (5-8). https://doi.org/10.1145/3437914.3437970

Although good assessment and feedback practices are widely recognised as crucial to learning, historical UK NSS results illustrate that current practices leave students dissatisfied the most in terms of their overall learning experience. This paper o... Read More about Student Perceptions of Assessment and Feedback - are they valid?.