Outputs (35)

Achieving goals using reward shaping and curriculum learning (2023)
Presentation / Conference
Studley, M., hansen, M., anca, M., thomas, J., & pedamonti, D. (2023, November). Achieving goals using reward shaping and curriculum learning. Paper presented at Future Technologies Conference, San Francisco

Real-time control for robotics is a popular research area in the reinforcement learning community. Through the use of techniques such as reward shaping, researchers have managed to train online agents across a multitude of domains. Despite these adva... Read More about Achieving goals using reward shaping and curriculum learning.

Embedding citizens within airborne microplastic and microfibre research (2023)
Journal Article
Williams, B., De Vito, L., Margarida Sardo, A., Pringle, K., Hansen, M., Taylor, M., …Hayes, E. (2023). Embedding citizens within airborne microplastic and microfibre research. Cambridge Prisms: Plastics, 1(e11), 1-5. https://doi.org/10.1017/plc.2023.11

Microplastics are ubiquitous in our environment but their presence in air is less well understood. Homes are likely a key source of airborne microplastics and microfibres to the environment owing to the frequent use and storage of plastics and textil... Read More about Embedding citizens within airborne microplastic and microfibre research.

Transformers and human-robot interaction for delirium detection (2023)
Conference Proceeding
Jeffcock, J., Hansen, M., & Ruiz Garate, V. (2023). Transformers and human-robot interaction for delirium detection. In 2023 ACM/IEEE International Conference on Human-Robot Interaction (466-474). https://doi.org/10.1145/3568162.3576971

An estimated 20% of patients admitted to hospital wards are affected by delirium. Early detection is recommended to treat underlying causes of delirium, however workforce strain in general wards often causes it to remain undetected. This work propose... Read More about Transformers and human-robot interaction for delirium detection.

A procedure for monitoring the phenological status of peach flowers with artificial vision (2022)
Presentation / Conference
Hansen, M., Veganzones, A., Lafuente, V., Barreiro, P., Lleo, L., & Val, J. (2022, December). A procedure for monitoring the phenological status of peach flowers with artificial vision. Paper presented at The XX CIGR World Congress 2022, Kyoto, Japan

Tree flowering is a major event in crop production as it anticipates season yield. However a number of issues may occur during the campaign such as frost, and/or irregular mineral nutrition, among other, that strongly affect this process. On the othe... Read More about A procedure for monitoring the phenological status of peach flowers with artificial vision.

Rapid identification of foodborne pathogens in limited resources settings using a handheld Raman spectroscopy device (2022)
Journal Article
Stratakos, A., & Hansen, M. (2022). Rapid identification of foodborne pathogens in limited resources settings using a handheld Raman spectroscopy device. Applied Sciences, 12(19), Article 9909. https://doi.org/10.3390/app12199909

Featured Application: Here, we report a practical and precise method for the identification of foodborne pathogenic bacteria using a Raman handheld device equipped with an orbital raster scan (ORS) technology that enables the system to generate a dis... Read More about Rapid identification of foodborne pathogens in limited resources settings using a handheld Raman spectroscopy device.

Improvements in learning to control perched landings (2022)
Journal Article
Fletcher, L., Clarke, R., Richardson, T., & Hansen, M. (2022). Improvements in learning to control perched landings. Aeronautical Journal, 126(1301), 1101-1123. https://doi.org/10.1017/aer.2022.48

Reinforcement learning has previously been applied to the problem of controlling a perched landing manoeuvre for a custom sweep-wing aircraft. Previous work showed that the use of domain randomisation to train with atmospheric disturbances improved t... Read More about Improvements in learning to control perched landings.

Towards machine vision for insect welfare monitoring and behavioural insights (2022)
Journal Article
Hansen, M. F., Oparaeke, A., Gallagher, R., Karimi, A., Tariq, F., & Smith, M. L. (2022). Towards machine vision for insect welfare monitoring and behavioural insights. Frontiers in Veterinary Science, 9, Article 835529. https://doi.org/10.3389/fvets.2022.835529

Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying stat... Read More about Towards machine vision for insect welfare monitoring and behavioural insights.

Vision based semantic runway segmentation from simulation with deep convolutional neural networks (2021)
Conference Proceeding
Quessy, A. D., Richardson, T. S., & Hansen, M. (2022). Vision based semantic runway segmentation from simulation with deep convolutional neural networks. https://doi.org/10.2514/6.2022-0680

Manned flight crew rely upon optical imagery to make sense of the world and carry out high level guidance, navigation & control tasks. To advance autonomous aircraft’s capabilities and safety, programmes need to be developed that aim to achieve pilot... Read More about Vision based semantic runway segmentation from simulation with deep convolutional neural networks.

Towards facial expression recognition for on-farm welfare assessment in pigs (2021)
Journal Article
Hansen, M. F., Baxter, E. M., Rutherford, K. M. D., Futro, A., Smith, M. L., & Smith, L. N. (2021). Towards facial expression recognition for on-farm welfare assessment in pigs. Agriculture, 11(9), Article 847. https://doi.org/10.3390/agriculture11090847

Animal welfare is not only an ethically important consideration in good animal husbandry but can also have a significant effect on an animal’s productivity. The aim of this paper was to show that a reduction in animal welfare, in the form of increase... Read More about Towards facial expression recognition for on-farm welfare assessment in pigs.

Contactless robust 3D palm-print identification using photometric stereo (2021)
Conference Proceeding
Smith, L. N., Langhof, M. P., Hansen, M. F., & Smith, M. L. (2021). Contactless robust 3D palm-print identification using photometric stereo. https://doi.org/10.1117/12.2595439

Palmprints are of considerable interest as a reliable biometric, since they offer significant advantages, such as greater user acceptance than fingerprint or iris recognition. 2D systems can be spoofed by a photograph of a hand; however, 3D avoids th... Read More about Contactless robust 3D palm-print identification using photometric stereo.