Mark F. Hansen
Mark F. Hansen
Professor, Centre for Machine Vision, Bristol Robotics Laboratory, UWE Bristol
Verified email at - Homepage
Cited by
Cited by
Towards on-farm pig face recognition using convolutional neural networks
MF Hansen, ML Smith, LN Smith, MG Salter, EM Baxter, M Farish, ...
Computers in Industry 98, 145-152, 2018
Automated monitoring of dairy cow body condition, mobility and weight using a single 3D video capture device
MF Hansen, ML Smith, LN Smith, KA Jabbar, D Forbes
Computers in industry 98, 14-22, 2018
The quiet revolution in machine vision-a state-of-the-art survey paper, including historical review, perspectives, and future directions
ML Smith, LN Smith, MF Hansen
Computers in Industry 130, 103472, 2021
3D face reconstructions from photometric stereo using near infrared and visible light
MF Hansen, GA Atkinson, LN Smith, ML Smith
Computer Vision and Image Understanding 114 (8), 942-951, 2010
Twins 3D face recognition challenge
V Vijayan, KW Bowyer, PJ Flynn, D Huang, L Chen, M Hansen, ...
2011 international joint conference on biometrics (IJCB), 1-7, 2011
Early and non-intrusive lameness detection in dairy cows using 3-dimensional video
KA Jabbar, MF Hansen, ML Smith, LN Smith
Biosystems engineering 153, 63-69, 2017
The photoface database
S Zafeiriou, M Hansen, G Atkinson, V Argyriou, M Petrou, M Smith, ...
CVPR 2011 WORKSHOPS, 132-139, 2011
Face recognition and verification using photometric stereo: The photoface database and a comprehensive evaluation
S Zafeiriou, GA Atkinson, MF Hansen, WAP Smith, V Argyriou, M Petrou, ...
IEEE transactions on information forensics and security 8 (1), 121-135, 2012
Multispectral imaging for presymptomatic analysis of light leaf spot in oilseed rape
C Veys, F Chatziavgerinos, A AlSuwaidi, J Hibbert, M Hansen, G Bernotas, ...
Plant methods 15, 1-12, 2019
A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth
G Bernotas, LCT Scorza, MF Hansen, IJ Hales, KJ Halliday, LN Smith, ...
GigaScience 8 (5), giz056, 2019
Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field
LN Smith, W Zhang, MF Hansen, IJ Hales, ML Smith
Computers in industry 97, 122-131, 2018
Broad-leaf weed detection in pasture
W Zhang, MF Hansen, TN Volonakis, M Smith, L Smith, J Wilson, ...
2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC …, 2018
Image segmentation of underfloor scenes using a mask regions convolutional neural network with two-stage transfer learning
GA Atkinson, W Zhang, MF Hansen, ML Holloway, AA Napier
Automation in Construction 113, 103118, 2020
Weed classification in grasslands using convolutional neural networks
LN Smith, A Byrne, MF Hansen, W Zhang, ML Smith
Applications of Machine Learning 11139, 334-344, 2019
Non-intrusive automated measurement of dairy cow body condition using 3D video
M Hansen, M Smith, L Smith, I Hales, D Forbes
Proceedings of the Machine Vision of Animals and their Behaviour (MVAB), 1.1-1.8, 2015
Towards facial expression recognition for on-farm welfare assessment in pigs
MF Hansen, EM Baxter, KMD Rutherford, A Futro, ML Smith, LN Smith
Agriculture 11 (9), 847, 2021
Photometric stereo for three-dimensional leaf venation extraction
W Zhang, MF Hansen, M Smith, L Smith, B Grieve
Computers in Industry 98, 56-67, 2018
Reinforcement learning for a perched landing in the presence of wind
LJ Fletcher, RJ Clarke, TS Richardson, M Hansen
AIAA Scitech 2021 Forum, 1282, 2021
Biologically inspired 3D face recognition from surface normals
MF Hansen, GA Atkinson
Procedia Computer Science 2, 26-34, 2010
Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights
MF Hansen, A Oparaeke, R Gallagher, A Karimi, F Tariq, ML Smith
Frontiers in Veterinary Science 9, 835529, 2022
The system can't perform the operation now. Try again later.
Articles 1–20