Outputs (2293)

Fuzzy-Based Ensemble Method for Robust Concept Drift Detection in Multivariate Time Series (2025)
Presentation / Conference Contribution
Tavares, L. G., Lima, J., Melo, M., Chen, C., Garibaldi, J. M., Scatena, G. D. S., Costa, A. H. R., Gomi, E. S., Salles, R., Pacitti, E., Santos, I., Siqueira, I. G., Carvalho, D., Coutinho, R., Porto, F., & Ogasawara, E. (2025, June). Fuzzy-Based Ensemble Method for Robust Concept Drift Detection in Multivariate Time Series. Presented at International Joint Conference on Neural Networks (IJCNN 2025), Rome, Italy

Concept drift detection (CDD) is the general problem of identifying significant changes in streaming data distribution over time. Effective drift detection is important in industrial processes such as oil and gas exploration to mitigate financial los... Read More about Fuzzy-Based Ensemble Method for Robust Concept Drift Detection in Multivariate Time Series.

Directed Perturbations for Efficient Learning of Surrogate Losses (2025)
Presentation / Conference Contribution
Cargan, T. R., Landa-Silva, D., & Triguero, I. (2025, June). Directed Perturbations for Efficient Learning of Surrogate Losses. Presented at International Joint Conference on Neural Networks (IJCNN 2025), Rome, Italy

Decision-Focused Learning (DFL) is a paradigm to learn neural network-based predictive models tailored to a specific optimisation problem. A key challenge for DFL methods lies in the non-differentiable nature of most optimisation problems. Recent sol... Read More about Directed Perturbations for Efficient Learning of Surrogate Losses.

A labeled Clinical-MRI dataset of Nigerian brains (2025)
Journal Article
Wogu, E., Filima, P., Caron, B., Deabler, D., Herholz, P., Leal, C., Mehboob, M. F., Kim, S., Gosain, A., Flexwala, A., Hayashi, S., Akintoye, S., Ogoh, G., Godwin, T., Eke, D., & Pestilli, F. (2025). A labeled Clinical-MRI dataset of Nigerian brains. Scientific Data, 12(3), Article 518. https://doi.org/10.1038/s41597-025-04743-0

There is currently a paucity of neuroimaging data from the African continent, limiting the diversity of data from a significant proportion of the global population. This in turn diminishes global health research and innovation. To address this issue,... Read More about A labeled Clinical-MRI dataset of Nigerian brains.

High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields (2025)
Journal Article
Pound, M. P., Stuart, L. A., Wells, D. M., Atkinson, J. A., Castle-Green, S., & Walker, J. (2025). High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields. GigaScience, 14, Article giaf022. https://doi.org/10.1093/gigascience/giaf022

Background: The reconstruction of 3-dimensional (3D) plant models can offer advantages over traditional 2-dimensional approaches by more accurately capturing the complex structure and characteristics of different crops. Conventional 3D reconstruction... Read More about High-fidelity wheat plant reconstruction using 3D Gaussian splatting and neural radiance fields.

Dancing with a Robot: An Experimental Study of Child-Robot Interaction in a Performative Art Setting (2025)
Presentation / Conference Contribution
Ngo, V. Z. H., Patel, R., Ramchurn, R., Chamberlain, A., & Kucukyilmaz, A. (2024, October). Dancing with a Robot: An Experimental Study of Child-Robot Interaction in a Performative Art Setting. Presented at International Conference on Social Robotics (ICSR), Odense, Denmark

This paper presents an evaluation of 18 children's in-the-wild experiences with the autonomous robot arm performer NED (Never-Ending Dancer) within the Thingamabobas installation, showcased across the UK. We detail NED's design, including costume, be... Read More about Dancing with a Robot: An Experimental Study of Child-Robot Interaction in a Performative Art Setting.

How Artists Improvise and Provoke Robotics (2025)
Presentation / Conference Contribution
Benford, S., Garrett, R., Schneiders, E., Tennent, P., Chamberlain, A., Avila, J., Brundell, P., & Castle-Green, S. (2024, October). How Artists Improvise and Provoke Robotics. Poster presented at 16th International Conference on Social Robotics + AI (ICSR + AI) 2024, Odense, Denmark

We explore transdisciplinary collaborations between artists and roboticists across a portfolio of artworks. Brendan Walker's Bronco-matic was a breath controlled mechanical rodeo bull ride. Blast Theory's Cat Royale deployed a robot arm to play with... Read More about How Artists Improvise and Provoke Robotics.

Meeting of minds: Imagining the future of child and youth mental health research from an early career perspective (2025)
Journal Article
Knight, R., Demkowicz, O., Sprecher, E. A., Gomez Bergin, A. D., Marzetti, H., Petersen, K. J., Kara, B., Sawrikar, V., White, H. J., Parsonage-Harrison, J., Wolstencroft, J., Reardon, T., March, A., McIver, L., Jones, H. J., Clarke, T., Breedvelt, J., & Chatburn, E. (in press). Meeting of minds: Imagining the future of child and youth mental health research from an early career perspective. British Journal of Psychiatry,

Child and youth mental health is an international public health and research priority. We are an interdisciplinary and cross-sectoral network of UK-based early career researchers (ECRs) with an interest in child and youth mental health research. In t... Read More about Meeting of minds: Imagining the future of child and youth mental health research from an early career perspective.

Practical aberration correction using deep transfer learning with limited experimental data (2025)
Journal Article
Kok, Y. E., Bentley, A., Parkes, A. J., Somekh, M. G., Wright, A. J., & Pound, M. P. (2025). Practical aberration correction using deep transfer learning with limited experimental data. Optics Express, 33(6), 14431-14444. https://doi.org/10.1364/oe.557993

Adaptive optics is a technique for correcting aberrations and improving image quality. When adaptive optics was first used in microscopy, it was common to rely on iterative approaches to determine the aberrations present. It is advantageous to avoid... Read More about Practical aberration correction using deep transfer learning with limited experimental data.

Cloud Detection Challenge - Methods and Results (2025)
Journal Article
Chisari, A. B., Guarnera, L., Ortis, A., Patatu, W. C., Casella, B., Naso, L., Puglisi, G., Del Zoppo, V., Giuffrida, M. V., & Battiato, S. (2025). Cloud Detection Challenge - Methods and Results. IEEE Access, https://doi.org/10.1109/ACCESS.2025.3553422

Accurate cloud detection is critical for advancing atmospheric monitoring and meteorological forecasting. This paper presents the Cloud Detection Challenge, an initiative aimed at enhancing cloud detection through innovative solutions using lidar-bas... Read More about Cloud Detection Challenge - Methods and Results.

Tangles: Unpacking Extended Collision Experiences with Soma Trajectories (2025)
Journal Article
Benford, S., Garrett, R., Li, C., Tennent, P., NÚÑEZ-PACHECO, C., Núñez-Pacheco, C., Kucukyilmaz, A., Tsaknaki, V., HÖÖK, K., Höök, K., Caleb-Solly, P., Marshall, J., Schneiders, E., Popova, K., & Afana, J. (in press). Tangles: Unpacking Extended Collision Experiences with Soma Trajectories. ACM Transactions on Computer-Human Interaction, https://doi.org/10.1145/3723875

We reappraise the idea of colliding with robots, moving from a position that tries to avoid or mitigate collisions to one that considers them an important facet of human interaction. We report on a soma design workshop that explored how our bodies co... Read More about Tangles: Unpacking Extended Collision Experiences with Soma Trajectories.