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Daniel Ward
Daniel Ward
The Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Verified email at data61.csiro.au
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Cited by
Cited by
Year
Plant disease detection using hyperspectral imaging
P Moghadam, D Ward, E Goan, S Jayawardena, P Sikka, E Hernandez
2017 International Conference on Digital Image Computing: Techniques and …, 2017
1502017
Deep leaf segmentation using synthetic data
D Ward, P Moghadam, N Hudson
arXiv preprint arXiv:1807.10931, 2018
1382018
Learning arbitrary-goal fabric folding with one hour of real robot experience
R Lee, D Ward, V Dasagi, A Cosgun, J Leitner, P Corke
Conference on Robot Learning, 2317-2327, 2021
632021
Temporally coherent embeddings for self-supervised video representation learning
J Knights, B Harwood, D Ward, A Vanderkop, O Mackenzie-Ross, ...
2020 25th International Conference on Pattern Recognition (ICPR), 8914-8921, 2021
442021
Scalable learning for bridging the species gap in image-based plant phenotyping
D Ward, P Moghadam
Computer Vision and Image Understanding 197, 103009, 2020
302020
On the use of genome‐wide data to model and date the time of anthropogenic hybridisation: An example from the Scottish wildcat
J Howard‐McCombe, D Ward, AC Kitchener, D Lawson, HV Senn, ...
Molecular Ecology 30 (15), 3688-3702, 2021
282021
Investigating the impact of model misspecification in neural simulation-based inference
P Cannon, D Ward, SM Schmon
arXiv preprint arXiv:2209.01845, 2022
232022
Robust neural posterior estimation and statistical model criticism
D Ward, P Cannon, M Beaumont, M Fasiolo, S Schmon
Advances in Neural Information Processing Systems 35, 33845-33859, 2022
202022
Deep leaf segmentation using synthetic data. arXiv 2018
D Ward, P Moghadam, N Hudson
arXiv preprint arXiv:1807.10931, 0
6
Synthetic arabidopsis dataset
D Ward, P Moghadam
CSIRO. Data Collection., 2018
42018
Using synthetic data to boost automated image-based plant phenotyping
D Ward, P Moghadam, N Hudson
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Articles 1–11