All Outputs (6)

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.

Fast global interactive volume segmentation with regional supervoxel descriptors (2016)
Journal Article
Luengo, I., Basham, M., & French, A. P. (2016). Fast global interactive volume segmentation with regional supervoxel descriptors. Proceedings of SPIE, 9784, Article 97842D. https://doi.org/10.1117/12.2216382

In this paper we propose a novel approach towards fast multi-class volume segmentation that exploits supervoxels in order to reduce complexity, time and memory requirements. Current methods for biomedical image segmentation typically require either c... Read More about Fast global interactive volume segmentation with regional supervoxel descriptors.