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All Outputs (42)

Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities (2024)
Journal Article
Channa, A. A., Munir, K., Hansen, M., & Tariq, M. F. (2024). Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities. Encyclopedia, 4(1), 313-336. https://doi.org/10.3390/encyclopedia4010023

Environment changes, water scarcity, soil depletion, and urbanisation are making it harder to produce food using traditional methods in various regions and countries. Aquaponics is emerging as a sustainable food production system that produces fish a... Read More about Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities.

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.

The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions (2021)
Journal Article
Smith, M. L., Smith, L. N., & Hansen, M. F. (2021). The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions. Computers in Industry, 130, Article 103472. https://doi.org/10.1016/j.compind.2021.103472

Over the past few years, what might not unreasonably be described as a true revolution has taken place in the field of machine vision, radically altering the way many things had previously been done and offering new and exciting opportunities for tho... Read More about The quiet revolution in machine vision - A state-of-the-art survey paper, including historical review, perspectives, and future directions.

Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells (2021)
Journal Article
Gynn, L., Lamb-Riddell, K., Cox, T., Hansen, M., Conway, M., & May, J. (2021). Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells. British Journal of Haematology, 193(S1), 46-47

Mesenchymal stromal cells (MSC) protect leukaemic cells from drug-induced toxicity within the bone marrow niche, with increasing evidence of leukaemic impact on supportive stroma. The nucleoside analogue, cytarabine (ara-C), is a front-line agent for... Read More about Shedding smart light on the effectiveness of chemotherapy: using Raman spectroscopy and machine learning to differentiate the effects of Cytarabine toxicity and crosstalk of leukaemic and bone marrow stromal cells.

Reinforcement learning for a perched landing in the presence of wind (2021)
Conference Proceeding
Fletcher, L. J., Clarke, R. J., Richardson, T. S., & Hansen, M. (2021). Reinforcement learning for a perched landing in the presence of wind. . https://doi.org/10.2514/6.2021-1282

Previous research by the University of Bristol's Flight Lab demonstrated the feasibility of using reinforcement learning to generate a controller to perform an agile perched landing flight manoeuvre. However, flight testing demonstrated the limits of... Read More about Reinforcement learning for a perched landing in the presence of wind.

Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning (2020)
Journal Article
Atkinson, G. A., Zhang, W., Hansen, M. F., Holloway, M. L., & Napier, A. A. (2020). Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning. Automation in Construction, 113, Article 103118. https://doi.org/10.1016/j.autcon.2020.103118

© 2020 Elsevier B.V. Enclosed spaces are common in built structures but pose a challenge to many forms of manual or robotic surveying and maintenance tasks. Part of this challenge is to train robot systems to understand their environment without huma... Read More about Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning.

Weed classification in grasslands using convolutional neural networks (2019)
Conference Proceeding
Smith, L. N., Byrne, A., Hansen, M. F., Zhang, W., & Smith, M. L. (2019). Weed classification in grasslands using convolutional neural networks. . https://doi.org/10.1117/12.2530092

Automatic identification and selective spraying of weeds (such as dock) in grass can provide very significant long-term ecological and cost benefits. Although machine vision (with interface to suitable automation) provides an effective means of achie... Read More about Weed classification in grasslands using convolutional neural networks.

Surface normals based landmarking for 3D face recognition using photometric stereo captures (2019)
Conference Proceeding
Gao, J., Hansen, M., Smith, M., & Evans, A. N. (2019). Surface normals based landmarking for 3D face recognition using photometric stereo captures. In Proceedings of the 2019 3rd International Conference on Biometric Engineering and Applications. , (43-47). https://doi.org/10.1145/3345336.3345339

In recent decades, many 3D data acquisition methods have been developed to provide accurate and cost-effective 3D captures of the human face. An example system, which can accommodate both research and commercial applications, is the Photoface device.... Read More about Surface normals based landmarking for 3D face recognition using photometric stereo captures.

Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape (2019)
Journal Article
Veys, C., Chatziavgerinos, F., AlSuwaidi, A., Hibbert, J., Hansen, M., Bernotas, G., …Grieve, B. (2019). Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape. Plant Methods, 15, Article 4. https://doi.org/10.1186/s13007-019-0389-9

Background: The use of spectral imaging within the plant phenotyping and breeding community has been increasing due its utility as a non-invasive diagnostic tool. However, there is a lack of imaging systems targeted specifically at plant science duti... Read More about Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape.

A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth (2019)
Journal Article
Bernotas, G., Scorza, L. C., Hansen, M. F., Hales, I. J., Halliday, K. J., Smith, L. N., …McCormick, A. J. (2019). A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth. GigaScience, 8(5), Article giz056. https://doi.org/10.1093/gigascience/giz056

© The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distri... Read More about A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth.