All Outputs (25)

Domain Adaptation of Synthetic Images for Wheat Head Detection (2021)
Journal Article
Hartley, Z. K., & French, A. P. (2021). Domain Adaptation of Synthetic Images for Wheat Head Detection. Plants, 10(12), Article 2633. https://doi.org/10.3390/plants10122633

Wheat head detection is a core computer vision problem related to plant phenotyping that in recent years has seen increased interest as large-scale datasets have been made available for use in research. In deep learning problems with limited training... Read More about Domain Adaptation of Synthetic Images for Wheat Head Detection.

RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures (2019)
Journal Article
Yasrab, R., Atkinson, J. A., Wells, D. M., French, A. P., Pridmore, T. P., & Pound, M. P. (2019). RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures. GigaScience, 8(11), https://doi.org/10.1093/gigascience/giz123

© The Author(s) 2019. Published by Oxford University Press. BACKGROUND: In recent years quantitative analysis of root growth has become increasingly important as a way to explore the influence of abiotic stress such as high temperature and drought on... Read More about RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures.

A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram (2019)
Journal Article
Bellos, D., Basham, M., Pridmore, T., & French, A. P. (2019). A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram. Journal of Synchrotron Radiation, 26(3), 839-853. https://doi.org/10.1107/s1600577519003448

We designed a convolutional neural network to quickly and accurately upscale the sinograms of x-ray tomograms captured with a low number of projections; effectively increasing the number of projections. This is particularly useful for tomograms that... Read More about A convolutional neural network for fast upsampling of undersampled tomograms in X-ray CT time-series using a representative highly sampled tomogram.

Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling (2019)
Journal Article
Gibbs, J., French, A., Murchie, E., Wells, D., Pound, M., & Pridmore, T. (2020). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 17(6), 1907-1917. https://doi.org/10.1109/TCBB.2019.2896908

Plant phenotyping is the quantitative description of a plant’s physiological, biochemical and anatomical status which can be used in trait selection and helps to provide mechanisms to link underlying genetics with yield. Here, an active vision- based... Read More about Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling.

Deep Hourglass for Brain Tumor Segmentation (2019)
Book Chapter
Benson, E., Pound, M. P., French, A. P., Jackson, A. S., & Pridmore, T. P. (2019). Deep Hourglass for Brain Tumor Segmentation. In BrainLes 2018: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (419-428). Springer. https://doi.org/10.1007/978-3-030-11726-9_37

The segmentation of a brain tumour in an MRI scan is a challenging task, in this paper we present our results for this problem via the BraTS 2018 challenge, consisting of 210 high grade glioma (HGG) and 75 low grade glioma (LGG) volumes for training.... Read More about Deep Hourglass for Brain Tumor Segmentation.

Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction (2018)
Journal Article
Gibbs, J., Pound, M., French, A. P., Wells, D. M., Murchie, E., & Pridmore, T. (2018). Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction. Plant Physiology, 178(2), 524-534. https://doi.org/10.1104/pp.18.00664

© 2018 American Society of Plant Biologists. All rights reserved. Three-dimensional (3D) computer-generated models of plants are urgently needed to support both phenotyping and simulation-based studies such as photosynthesis modeling. However, the co... Read More about Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction.

Enhancing supervised classifications with metamorphic relations (2018)
Conference Proceeding
Xu, L., Towey, D., French, A. P., Benford, S., Zhou, Z. Q., & Chen, T. Y. (2018). Enhancing supervised classifications with metamorphic relations. In MET '18: Proceedings of the 3rd International Workshop on Metamorphic Testing (46-53). https://doi.org/10.1145/3193977.3193978

We report on a novel use of metamorphic relations (MRs) in machine learning: instead of conducting metamorphic testing, we use MRs for the augmentation of the machine learning algorithms themselves. In particular, we report on how MRs can enable enha... Read More about Enhancing supervised classifications with metamorphic relations.

Recognizing the Presence of Hidden Visual Markers in Digital Images (2017)
Conference Proceeding
Xu, L., French, A. P., Towey, D., & Benford, S. (2017). Recognizing the Presence of Hidden Visual Markers in Digital Images. In Thematic Workshops '17: Proceedings of the on Thematic Workshops of ACM Multimedia 2017 (210-218). https://doi.org/10.1145/3126686.3126761

As the promise of Virtual and Augmented Reality (VR and AR) becomes more realistic, an interesting aspect of our enhanced living environment includes the availability — indeed the potential ubiquity — of scannable markers. Such markers could represen... Read More about Recognizing the Presence of Hidden Visual Markers in Digital Images.

Deep learning for multi-task plant phenotyping (2017)
Conference Proceeding
Pound, M. P., Atkinson, J. A., Wells, D. M., Pridmore, T. P., & French, A. P. (2017). Deep learning for multi-task plant phenotyping. In Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017 (2055-2063). https://doi.org/10.1109/ICCVW.2017.241

Plant phenotyping has continued to pose a challenge to computer vision for many years. There is a particular demand to accurately quantify images of crops, and the natural variability and structure of these plants presents unique difficulties. Recent... Read More about Deep learning for multi-task plant phenotyping.

Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress (2017)
Journal Article
Lowe, A., Harrison, N., & French, A. P. (2017). Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress. Plant Methods, 13, Article 80. https://doi.org/10.1186/s13007-017-0233-z

This review explores how imaging techniques are being developed with a focus on deployment for crop monitoring methods. Imaging applications are discussed in relation to both field and glasshouse-based plants, and techniques are sectioned into ‘healt... Read More about Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress.

Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench (2017)
Journal Article
Darrow, M. C., Luengo, I., Basham, M., Spink, M. C., Irvine, S., French, A. P., …Duke, E. M. (2017). Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench. Journal of Visualized Experiments, Article e56162. https://doi.org/10.3791/56162

Segmentation is the process of isolating specific regions or objects within an imaged volume, so that further study can be undertaken on these areas of interest. When considering the analysis of complex biological systems, the segmentation of three-d... Read More about Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench.

Deep machine learning provides state-of-the-art performance in image-based plant phenotyping (2017)
Journal Article
Pound, M. P., Atkinson, J. A., Townsend, A. J., Wilson, M. H., Griffiths, M., Jackson, A. S., …French, A. P. (2017). Deep machine learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience, 6(10), Article gix083. https://doi.org/10.1093/gigascience/gix083

© The Author 2017. In plant phenotyping, it has become important to be able to measure many features on large image sets in order to aid genetic discovery. The size of the datasets, now often captured robotically, often precludes manual inspection, h... Read More about Deep machine learning provides state-of-the-art performance in image-based plant phenotyping.

AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping (2017)
Journal Article
Pound, M. P., Fozard, S., Torres Torres, M., Forde, B. G., & French, A. P. (2017). AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping. Plant Methods, 13(1), Article 12. https://doi.org/10.1186/s13007-017-0161-y

Background: Computer-based phenotyping of plants has risen in importance in recent years. Whilst much software has been written to aid phenotyping using image analysis, to date the vast majority has been only semi-automatic. However, such interaction... Read More about AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping.

The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology (2017)
Journal Article
Burrell, T., Fozard, S., Holroyd, G. H., French, A. P., Pound, M. P., Bigley, C. J., …Forde, B. G. (2017). The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology. Plant Methods, 13(1), Article 10. https://doi.org/10.1186/s13007-017-0158-6

Background Chemical genetics provides a powerful alternative to conventional genetics for understanding gene function. However, its application to plants has been limited by the lack of a technology that allows detailed phenotyping of whole-seedling... Read More about The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology.

SuRVoS: Super-Region Volume Segmentation workbench (2017)
Journal Article
Luengo, I., Darrow, M. C., Spink, M. C., Sun, Y., Dai, W., He, C. Y., …French, A. P. (2017). SuRVoS: Super-Region Volume Segmentation workbench. Journal of Structural Biology, 198(1), 43-53. https://doi.org/10.1016/j.jsb.2017.02.007

Segmentation of biological volumes is a crucial step needed to fully analyse their scientific content. Not having access to convenient tools with which to segment or annotate the data means many biological volumes remain under-utilised. Automatic seg... Read More about SuRVoS: Super-Region Volume Segmentation workbench.

Selective labeling: identifying representative sub-volumes for interactive segmentation (2016)
Conference Proceeding
Luengo, I., Basham, M., & French, A. P. (2016). Selective labeling: identifying representative sub-volumes for interactive segmentation. In Patch-based Techniques in Medical Imaging (17-24). https://doi.org/10.1007/978-3-319-47118-1_3

Automatic segmentation of challenging biomedical volumes with multiple objects is still an open research field. Automatic approaches usually require a large amount of training data to be able to model the complex and often noisy appearance and struct... Read More about Selective labeling: identifying representative sub-volumes for interactive segmentation.

SMURFS: Superpixels from multi-scale refinement of super-regions (2016)
Conference Proceeding
Luengo, I., Basham, M., & French, A. P. (2016). SMURFS: Superpixels from multi-scale refinement of super-regions. In Proceedings of the British Machine Vision Conference 2016. https://doi.org/10.5244/C.30.4

Recent applications in computer vision have come to rely on superpixel segmentation as a pre-processing step for higher level vision tasks, such as object recognition, scene labelling or image segmentation. Here, we present a new algorithm, Superpixe... Read More about SMURFS: Superpixels from multi-scale refinement of super-regions.

Approaches to three-dimensional reconstruction of plant shoot topology and geometry (2016)
Journal Article
Gibbs, J., Pound, M. P., French, A. P., Wells, D. M., Murchie, E. H., & Pridmore, T. P. (2016). Approaches to three-dimensional reconstruction of plant shoot topology and geometry. Functional Plant Biology, 44(1), 62-75. https://doi.org/10.1071/FP16167

There are currently 805 million people classified as chronically undernourished, and yet the World’s population is still increasing. At the same time, global warming is causing more frequent and severe flooding and drought, thus destroying crops and... Read More about Approaches to three-dimensional reconstruction of plant shoot topology and geometry.

Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping (2016)
Working Paper
Pound, M. P., Burgess, A. J., Wilson, M. H., Atkinson, J. A., Griffiths, M., Jackson, A. S., …French, A. P. Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping

Deep learning is an emerging field that promises unparalleled results on many data analysis problems. We show the success offered by such techniques when applied to the challenging problem of image-based plant phenotyping, and demonstrate state-of-th... Read More about Deep Machine Learning provides state-of-the-art performance in image-based plant phenotyping.

A patch-based approach to 3D plant shoot phenotyping (2016)
Journal Article
Pound, M. P., French, A. P., Fozard, J. A., Murchie, E. H., & Pridmore, T. P. (2016). A patch-based approach to 3D plant shoot phenotyping. Machine Vision and Applications, 27(5), 767-779. https://doi.org/10.1007/s00138-016-0756-8

The emerging discipline of plant phenomics aims to measure key plant characteristics, or traits, though as yet the set of plant traits that should be measured by automated systems is not well defined. Methods capable of recovering generic representat... Read More about A patch-based approach to 3D plant shoot phenotyping.