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Outputs (835)

A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification (2023)
Journal Article
Hong, Q., Lin, L., Li, Z., Li, Q., Yao, J., Wu, Q., Liu, K., & Tian, J. (in press). A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2023.3280646

Detecting pneumonia, especially coronavirus disease 2019 (COVID-19), from chest X-ray (CXR) images is one of the most effective ways for disease diagnosis and patient triage. The application of deep neural networks (DNNs) for CXR image classification... Read More about A Distance Transformation Deep Forest Framework With Hybrid-Feature Fusion for CXR Image Classification.

Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning (2023)
Journal Article
Chatterjee, J., Alvela Nieto, M. T., Gelbhardt, H., Dethlefs, N., Ohlendorf, J. H., Greulich, A., & Thoben, K. D. (2023). Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning. Environmental Data Science, 2, 1-15. https://doi.org/10.1017/eds.2023.9

Wind energy's ability to liberate the world from conventional sources of energy relies on lowering the significant costs associated with the maintenance of wind turbines. Since icing events on turbine rotor blades are a leading cause of operational f... Read More about Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning.

Learning Fair Representations through Uniformly Distributed Sensitive Attributes (2023)
Presentation / Conference Contribution
Kenfack, P., Rivera, A., Khan, A., & Mazzara, M. (2023, February). Learning Fair Representations through Uniformly Distributed Sensitive Attributes. Presented at 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), Raleigh, NC, USA

Machine Learning (ML) models trained on biased data can reproduce and even amplify these biases. Since such models are deployed to make decisions that can affect people's lives, ensuring their fairness is critical. One approach to mitigate possi... Read More about Learning Fair Representations through Uniformly Distributed Sensitive Attributes.

Teaching students using Design-First Test-Driven Development (2023)
Presentation / Conference Contribution
Dixon, J., Brayshaw, M., Gordon, N., Grey, S., Parker, D., & Tompsett, B. (2022, June). Teaching students using Design-First Test-Driven Development. Presented at INSPIRE XXVII: E-Learning for Sustainabilty and Education Beyond Pandemic, Online

This paper explores a test-driven approach to teaching within Higher Education. Test-driven here is derived from the Software Engineering approach, where the test cases for software are defined prior to the software being fully developed. The emphasi... Read More about Teaching students using Design-First Test-Driven Development.

Teaching Sustainable Computing Remotely (2023)
Presentation / Conference Contribution
Gordon, N. (2022, June). Teaching Sustainable Computing Remotely. Presented at INSPIRE XXVII - e-Learning for Sustainability and Education Beyond Pandemic, Online

This paper explores experiences of teaching sustainable computing remotely during the Coronavirus pandemic. The unanticipated rapid pivot to online learning meant that courses with traditional teaching, or blended approaches had to be adapted to be d... Read More about Teaching Sustainable Computing Remotely.

Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models (2023)
Presentation / Conference Contribution
Mboli, J. S., Thakker, D., & Mishra, J. (2023, April). Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models. Presented at International Conference on Enterprise Information Systems, ICEIS - Proceedings, Prague, Czech Republic

The circular economy (CE) is preferred to linear economy (LE) as it aims to keep resources in use for as long as possible, extracting maximum value before recovering and regenerating them. This reduces the need to extract new raw materials and reduce... Read More about Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models.

Design and Adaptive Compliance Control of a Wearable Walk Assist Device (2023)
Presentation / Conference Contribution
Shah, S. H., Alam, M. S., Arsalan, M., Ul Haq, I., Khan, S. G., & Iqbal, J. (2023, March). Design and Adaptive Compliance Control of a Wearable Walk Assist Device. Presented at 2023 International Conference on Robotics and Automation in Industry (ICRAI), Peshawar, Pakistan

The ability to walk independently is a predominant feature that human beings are bestowed with by nature. People with moving disabilities face many challenges in day-to-day activities and they have to rely on others to perform their day-to-day activi... Read More about Design and Adaptive Compliance Control of a Wearable Walk Assist Device.

Information Rich Voxel Grid for Use in Heterogeneous Multi-Agent Robotics (2023)
Journal Article
Balding, S., Gning, A., Cheng, Y., & Iqbal, J. (2023). Information Rich Voxel Grid for Use in Heterogeneous Multi-Agent Robotics. Applied Sciences, 13(8), Article 5065. https://doi.org/10.3390/app13085065

Robotic agents are now ubiquitous in both home and work environments; moreover, the degree of task complexity they can undertake is also increasing exponentially. Now that advanced robotic agents are commonplace, the question for utilisation becomes... Read More about Information Rich Voxel Grid for Use in Heterogeneous Multi-Agent Robotics.

Precision agricultural robotic sprayer with real-time Tobacco recognition and spraying system based on deep learning (2023)
Journal Article
Nasir, F. E., Tufail, M., Haris, M., Iqbal, J., Khan, S., & Khan, M. T. (2023). Precision agricultural robotic sprayer with real-time Tobacco recognition and spraying system based on deep learning. PLoS ONE, 18(3 MARCH), Article e0283801. https://doi.org/10.1371/journal.pone.0283801

Precision agricultural techniques try to prevent either an excessive or inadequate application of agrochemicals during pesticide application. In recent years, it has become popular to combine traditional agricultural practices with artificial intelli... Read More about Precision agricultural robotic sprayer with real-time Tobacco recognition and spraying system based on deep learning.

From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model (2023)
Journal Article
Kureshi, R. R., Thakker, D., Mishra, B. K., & Barnes, J. (2023). From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model. Sensors, 23(7), Article 3613. https://doi.org/10.3390/s23073613

The topic of indoor air pollution has yet to receive the same level of attention as ambient pollution. We spend considerable time indoors, and poorer indoor air quality affects most of us, particularly people with respiratory and other health conditi... Read More about From Raising Awareness to a Behavioural Change: A Case Study of Indoor Air Quality Improvement Using IoT and COM-B Model.