All Outputs (120)

Constructing a crowdsourced linked open knowledge base of Chinese history (2021)
Conference Proceeding
Sturgeon, D. (2021). Constructing a crowdsourced linked open knowledge base of Chinese history. . https://doi.org/10.23919/pnc53575.2021.9672294

This paper introduces a crowdsourced approach to knowledge base construction for historical data based upon annotation of historical source materials. Building on an existing digital library of premodern Chinese texts and adapting techniques from oth... Read More about Constructing a crowdsourced linked open knowledge base of Chinese history.

Modeling Autonomic Systems in the time of ML, DevOps and Microservices (2021)
Conference Proceeding
Bencomo, N. (2021). Modeling Autonomic Systems in the time of ML, DevOps and Microservices. . https://doi.org/10.1109/models-c53483.2021.00118

Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks (2021)
Conference Proceeding
Lieck, R., & Rohrmeier, M. (2021). Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks.

MedZip: 3D medical images lossless compressor using recurrent neural network (LSTM) (2021)
Conference Proceeding
Nagoor, O. H., Whittle, J., Deng, J., Mora, B., & Jones, M. W. (2021). MedZip: 3D medical images lossless compressor using recurrent neural network (LSTM). . https://doi.org/10.1109/icpr48806.2021.9413341

From a Series of (Un)fortunate Events to Global Explainability of Runtime Model-Based Self-Adaptive Systems (2021)
Conference Proceeding
Ullauri, J. M. P., García-Domínguez, A., & Bencomo, N. (2021). From a Series of (Un)fortunate Events to Global Explainability of Runtime Model-Based Self-Adaptive Systems. . https://doi.org/10.1109/models-c53483.2021.00127

Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead (2021)
Conference Proceeding
Bucchiarone, A., Cicchetti, A., Bencomo, N., Loria, E., & Marconi, A. (2021). Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead. . https://doi.org/10.1109/seams51251.2021.00028

Investigating the Potential Impact of Values on Requirements and Software Engineering (2021)
Conference Proceeding
Sutcliffe, A. G., Sawyer, P., Liu, W., & Bencomo, N. (2021). Investigating the Potential Impact of Values on Requirements and Software Engineering. . https://doi.org/10.1109/icse-seis52602.2021.00013

Simulating People Dynamics (2021)
Conference Proceeding
Saeed, R., Recupero, D. R., & Remagnino, P. (2021). Simulating People Dynamics. . https://doi.org/10.1109/ie51775.2021.9486478

Evidence for Teaching Practices that Broaden Participation for Women in Computing (2021)
Conference Proceeding
Morrison, B. B., Quinn, B. A., Bradley, S., Buffardi, K., Harrington, B., Hu, H. H., …Waite, J. (2021). Evidence for Teaching Practices that Broaden Participation for Women in Computing. In ITiCSE-WGR '21: Proceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education (57-131). https://doi.org/10.1145/3502870.3506568

Computing has, for many years, been one of the least demographically diverse STEM fields, particularly in terms of women's participation [12, 36]. The last decade has seen a proliferation of research exploring new teaching techniques and their effect... Read More about Evidence for Teaching Practices that Broaden Participation for Women in Computing.

Detecting Fine-Grained Emotions on Social Media during Major Disease Outbreaks: Health and Well-being before and during the COVID-19 Pandemic (2021)
Conference Proceeding
Aduragba, O. T., Yu, J., Cristea, A., & Shi, L. (2021). Detecting Fine-Grained Emotions on Social Media during Major Disease Outbreaks: Health and Well-being before and during the COVID-19 Pandemic.

Quickest Change Detection in the Presence of Transient Adversarial Attacks (2021)
Conference Proceeding
Vasantam, T., Towsley, D., & Veeravalli, V. V. (2021). Quickest Change Detection in the Presence of Transient Adversarial Attacks. . https://doi.org/10.1109/ciss50987.2021.9400287

“Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving (2021)
Conference Proceeding
Stelling, J., & Atapour-Abarghouei, A. (2021). “Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving. . https://doi.org/10.1109/bigdata52589.2021.9672033

Biases can filter into AI technology without our knowledge. Oftentimes, seminal deep learning networks champion increased accuracy above all else. In this paper, we attempt to alleviate biases encountered by semantic segmentation models in urban driv... Read More about “Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving.

Transforming Fake News: Robust Generalisable News Classification Using Transformers (2021)
Conference Proceeding
Blackledge, C., & Atapour-Abarghouei, A. (2021). Transforming Fake News: Robust Generalisable News Classification Using Transformers. . https://doi.org/10.1109/bigdata52589.2021.9671970

As online news has become increasingly popular and fake news increasingly prevalent, the ability to audit the veracity of online news content has become more important than ever. Such a task represents a binary classification challenge, for which tra... Read More about Transforming Fake News: Robust Generalisable News Classification Using Transformers.

Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking (2021)
Conference Proceeding
Carrell, S., & Atapour-Abarghouei, A. (2021). Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking. . https://doi.org/10.1109/bigdata52589.2021.9671378

The use of mobiles phones when driving has been a major factor when it comes to road traffic incidents and the process of capturing such violations can be a laborious task. Advancements in both modern object detection frameworks and high-performance... Read More about Identification of Driver Phone Usage Violations via State-of-the-Art Object Detection with Tracking.

Rank over Class: The Untapped Potential of Ranking in Natural Language Processing (2021)
Conference Proceeding
Atapour-Abarghouei, A., Bonner, S., & McGough, A. S. (2021). Rank over Class: The Untapped Potential of Ranking in Natural Language Processing. . https://doi.org/10.1109/bigdata52589.2021.9671386

Text classification has long been a staple within Natural Language Processing (NLP) with applications spanning across diverse areas such as sentiment analysis, recommender systems and spam detection. With such a powerful solution, it is often temptin... Read More about Rank over Class: The Untapped Potential of Ranking in Natural Language Processing.

Continuous Multi-modal Emotion Prediction in Video based on Recurrent Neural Network Variants with Attention (2021)
Conference Proceeding
Raju, J., Gaus, Y., & Breckon, T. (2021). Continuous Multi-modal Emotion Prediction in Video based on Recurrent Neural Network Variants with Attention. . https://doi.org/10.1109/icmla52953.2021.00115

Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery (2021)
Conference Proceeding
Webb, T., Bhowmik, N., Gaus, Y., & Breckon, T. (2021). Operationalizing Convolutional Neural Network Architectures for Prohibited Object Detection in X-Ray Imagery. . https://doi.org/10.1109/icmla52953.2021.00102

Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery (2021)
Conference Proceeding
Wang, Q., & Breckon, T. (2021). Contraband Materials Detection Within Volumetric 3D Computed Tomography Baggage Security Screening Imagery. . https://doi.org/10.1109/icmla52953.2021.00020

Robust 3D U-Net Segmentation of Macular Holes (2021)
Conference Proceeding
Frawley, J., Willcocks, C. G., Habib, M., Geenen, C., Steel, D. H., & Obara, B. (2021). Robust 3D U-Net Segmentation of Macular Holes. In A. Pakrashi, E. Rushe, M. H. Z. Bazargani, & B. Mac Namee (Eds.),

Macular holes are a common eye condition which result in visual impairment. We look at the application of deep convolutional neural networks to the problem of macular hole segmentation. We use the 3D U-Net architecture as a basis and experiment with... Read More about Robust 3D U-Net Segmentation of Macular Holes.

Session details: 1st International Workshop on Blockchain for Smart Cyber-Physical Systems (BlockCPS) (2021)
Conference Proceeding
(2021). Session details: 1st International Workshop on Blockchain for Smart Cyber-Physical Systems (BlockCPS). In G. S. Aujla, & A. Jindal (Eds.), . https://doi.org/10.1145/3517183