Mark Hansen's Outputs (46)

Co-creation in citizen science: Sharing learnings and good practice from an indoor, airborne microplastics project (2024)
Journal Article

HOMEs was a citizen science exploratory project, aimed at investigating the presence of airborne microplastics in people's homes. Participants placed passive samplers in their homes, using low-cost microscopes to see and take pictures of their sample... Read More about Co-creation in citizen science: Sharing learnings and good practice from an indoor, airborne microplastics project.

Universal bovine identification via depth data and deep metric learning (2024)
Journal Article

This paper proposes and evaluates, for the first time, a top-down (dorsal view), depth-only deep learning system for accurately identifying individual cattle and provides associated code, datasets, and training weights for immediate reproducibility.... Read More about Universal bovine identification via depth data and deep metric learning.

Airborne microplastic monitoring: Developing a simplified outdoor sampling approach using pollen monitoring equipment (2024)
Journal Article

A novel, yet simple, airborne microplastic (MP) sampling approach using global pollen monitoring equipment was applied to identify, characterise and quantify outdoor airborne MPs for the first time. Modification of Burkard spore trap tape adhesive pr... Read More about Airborne microplastic monitoring: Developing a simplified outdoor sampling approach using pollen monitoring equipment.

Machine vision and deep learning for robotic harvesting of shiitake mushrooms (2024)
Presentation / Conference Contribution

There is a substantial requirement for the modernisation of our agricultural practices. Current methods can be susceptible to labour shortages, damaging to the environment, and inefficient; and these factors can lead to food wastage so threatening fo... Read More about Machine vision and deep learning for robotic harvesting of shiitake mushrooms.

Optimisation of small-scale aquaponics systems using artificial intelligence and the IoT: Current status, challenges, and opportunities (2024)
Journal Article

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 Contribution

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

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.

Airborne Microplastics measurement: Putting people at the heart of the science (2023)
Presentation / Conference Contribution

Transformers and human-robot interaction for delirium detection (2023)
Presentation / Conference Contribution

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 Contribution

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

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

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

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)
Presentation / Conference Contribution

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

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)
Presentation / Conference Contribution

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

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)
Presentation / Conference Contribution

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)
Presentation / Conference Contribution

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

© 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.