Outputs (35)

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.

Broad-leaf weed detection in pasture (2018)
Conference Proceeding
Zhang, W., Hansen, M. F., Volonakis, T. N., Smith, M., Smith, L., Wilson, J., …Wright, G. (2018). Broad-leaf weed detection in pasture.

Weed control in pasture is a challenging problem that can be expensive and environmentally unfriendly. This paper proposes a novel method for recognition of broad-leaf weeds in pasture such that precision weed control can be achieved with reduced her... Read More about Broad-leaf weed detection in pasture.

Multispectral contactless 3D handprint acquisition for identification (2018)
Presentation / Conference
Hansen, M. F., Smith, L., & Smith, M. (2018, July). Multispectral contactless 3D handprint acquisition for identification. Paper presented at The 20th International Conference on Artificial Intelligence, 2018 World Congress in Computer Science, Computer Engineering, & Applied Computing, Las Vegas, USA

We present and experimentally demonstrate the potential effectiveness of a photometric stereo based high resolution system for capturing 3D handprints using visible light sources. The sub-surface vascular structures are also enhanced through the use... Read More about Multispectral contactless 3D handprint acquisition for identification.