Melvyn Smith's Outputs (114)

A novel system for automated continuous on-farm assessment of digital dermatitis using Artificial Intelligence (2025)
Journal Article

Digital dermatitis (DD) is a major cause of lameness in cattle, significantly affecting animal well-being and reducing productivity across the dairy industry. This paper introduces a novel system combining innovative hardware coupled with a two-stage... Read More about A novel system for automated continuous on-farm assessment of digital dermatitis using Artificial Intelligence.

Precision single-camera eye tracking towards cognitive health assessment (2025)
Presentation / Conference Contribution

Eye tracking has been increasingly recognised as a valuable
tool for assessing cognitive health. However, many existing eye tracking systems are often expensive, imprecise, and inconvenient, which limits their accessibility and effectiveness in clin... Read More about Precision single-camera eye tracking towards cognitive health assessment.

Machine vision and deep learning for robotic harvesting of shiitake mushrooms (2025)
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.

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.

Development of a gamified Simon task for machine learning and eye-tracking analysis of cognitive performance in early dementia diagnosis (2024)
Presentation / Conference Contribution

Introduction

Technologies leveraging machine learning are enabling the creation of efficient methods for the early detection of age-related neurodegeneration outside of a lab environment. Combining cognitive assessments with eye movement analysis... Read More about Development of a gamified Simon task for machine learning and eye-tracking analysis of cognitive performance in early dementia diagnosis.

IYOLO-FAM: Improved YOLOv8 with feature attention mechanism for cow behaviour detection (2024)
Presentation / Conference Contribution

We introduced IYOLO-FAM (Improved YOLOv8 with Feature Attention Mechanism) for detecting cow behaviours. By leveraging the robust YOLOv8 architecture improved with Feature Attention Mechanisms (FAM), Squeeze-and-Excitation (SE) blocks and data augmen... Read More about IYOLO-FAM: Improved YOLOv8 with feature attention mechanism for cow behaviour detection.

3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy (2024)
Presentation / Conference Contribution

The significant beneficial effects of physiotherapy as a treatment for a wide range of medical conditions, is well known. However, the challenge for already stressed healthcare systems to provide effective physiotherapy to an aging population, that h... Read More about 3D Machine vision and deep learning for enabling automated and sustainable assistive physiotherapy.

EM-COGLOAD: An investigation into age and cognitive load detection using eye tracking and deep learning (2024)
Journal Article

Alzheimer's Disease is the most prevalent neurodegenerative disease, and is a leading cause of disability among the elderly. Eye movement behaviour demonstrates potential as a non-invasive biomarker for Alzheimer's Disease, with changes detectable at... Read More about EM-COGLOAD: An investigation into age and cognitive load detection using eye tracking and deep learning.

A two-stage approach using YOLO for automated assessment of digital dermatitis within Dairy Cattle (2024)
Presentation / Conference Contribution

Digital dermatitis stands as a primary cause of lameness in dairy cows, significantly impacting various facets of productivity. This paper proposes an innovative two-stage vision system aimed at early detection of digital dermatitis (DD) lesions, ult... Read More about A two-stage approach using YOLO for automated assessment of digital dermatitis within Dairy Cattle.

Convolutional neural network ensemble learning for hyperspectral imaging-based blackberry fruit ripeness detection in uncontrolled farm environment (2024)
Journal Article

Fruit ripeness estimation models have for decades depended on spectral index features or colour-based features, such as mean, standard deviation, skewness, colour moments, and/or histograms for learning traits of fruit ripeness. Recently, few studies... Read More about Convolutional neural network ensemble learning for hyperspectral imaging-based blackberry fruit ripeness detection in uncontrolled farm environment.

Real-time livestock activity monitoring via fine-tuned faster R-CNN for multiclass cattle behaviour detection (2023)
Presentation / Conference Contribution

Automated cattle activity detection plays a pivotal role in modern livestock management, significantly impacting animal welfare and operational efficiency. This paper introduces an automated approach for cattle activity detection using advanced deep... Read More about Real-time livestock activity monitoring via fine-tuned faster R-CNN for multiclass cattle behaviour detection.

Predicting multiple-target search performance using eye movements and individual differences (2023)
Presentation / Conference Contribution

Accuracy in visual search – the process of detecting a target amongst distractors – is critical for life-saving career searches such as radiology and airport security. These searches often contain multiple targets (e.g., a tumour and a fracture) and... Read More about Predicting multiple-target search performance using eye movements and individual differences.

Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa (2022)
Presentation / Conference Contribution

Existing machine learning models for crop yield prediction model environmental data on the assumption that soil variables are unaffected by weather variables and therefore learn their intrinsic features independently. If the focus of crop yield predi... Read More about Maize yield predictive models and mobile-based decision support system for smallholder farmers in Africa.

Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective (2022)
Journal Article

Background and Objective: Diabetes mellitus is a metabolic disorder characterized by hyperglycemia, which results from the inadequacy of the body to secrete and respond to insulin. If not properly managed or diagnosed on time, diabetes can pose a ris... Read More about Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective.

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.

Eye centre localisation with convolutional neural networks in high- and low-resolution images (2022)
Journal Article

Eye centre localisation is critical to eye tracking systems of various forms and with applications in variety of disciplines. An active eye tracking approach can achieve a high accuracy by leveraging active illumination to gain an enhanced contrast o... Read More about Eye centre localisation with convolutional neural networks in high- and low-resolution images.

A robust machine learning framework for diabetes prediction (2021)
Presentation / Conference Contribution

Diabetes mellitus is a metabolic disorder characterized by hyperglycemia which results from the inadequacy of the body to secret and responds to insulin. If not properly managed or diagnosed on time, diabetes can pose a risk to vital body organs such... Read More about A robust machine learning framework for diabetes prediction.

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.

Quantitative potato tuber phenotyping by 3D imaging (2021)
Journal Article

The accurate phenotyping of the external quality attributes of potato tubers is important in potato breeding. Currently, the assessment of potato tuber shape, together with eye density and depth, are based on subjective naked eye visual evaluation. H... Read More about Quantitative potato tuber phenotyping by 3D imaging.

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.