All Outputs (6)

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.