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-the-art results for root and shoot feature identific...
| Main Authors: | Pound, Michael P., Burgess, Alexandra J., Wilson, Michael H., Atkinson, Jonathan A., Griffiths, Marcus, Jackson, Aaron S., Bulat, Adrian, Tzimiropoulos, Yorgos, Wells, Darren M., Murchie, Erik H., Pridmore, Tony P., French, Andrew P. |
|---|---|
| Format: | Other |
| Published: |
Cold Spring Harbor Laboratory
2016
|
| Online Access: | https://eprints.nottingham.ac.uk/41648/ |
Similar Items
Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
by: Pound, Michael P., et al.
Published: (2017)
by: Pound, Michael P., et al.
Published: (2017)
Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction
by: Pridmore, Tony P., et al.
Published: (2018)
by: Pridmore, Tony P., et al.
Published: (2018)
Deep learning for multi-task plant phenotyping
by: Pound, Michael P., et al.
Published: (2017)
by: Pound, Michael P., et al.
Published: (2017)
A patch-based approach to 3D plant shoot phenotyping
by: Pound, Michael P., et al.
Published: (2016)
by: Pound, Michael P., et al.
Published: (2016)
Automated recovery of 3D models of plant shoots from multiple colour images
by: Pound, Michael P., et al.
Published: (2014)
by: Pound, Michael P., et al.
Published: (2014)
Approaches to three-dimensional reconstruction of plant shoot topology and geometry
by: Gibbs, Jonathon, et al.
Published: (2016)
by: Gibbs, Jonathon, et al.
Published: (2016)
Three-dimensional reconstruction of plant shoots from multiple images using an active vision system
by: Gibbs, Jonathon, et al.
Published: (2015)
by: Gibbs, Jonathon, et al.
Published: (2015)
Uncovering the hidden half of plants using new advances in root phenotyping
by: Atkinson, Jonathan A., et al.
Published: (2019)
by: Atkinson, Jonathan A., et al.
Published: (2019)
The 4-dimensional plant: effects of wind-induced canopy movement on light fluctuations and photosynthesis
by: Burgess, Alexandra J., et al.
Published: (2016)
by: Burgess, Alexandra J., et al.
Published: (2016)
Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat
by: Atkinson, Jonathan A., et al.
Published: (2015)
by: Atkinson, Jonathan A., et al.
Published: (2015)
Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems
by: Burgess, Alexandra J., et al.
Published: (2017)
by: Burgess, Alexandra J., et al.
Published: (2017)
High-resolution three-dimensional structural data quantify the impact of photoinhibition on long-term carbon gain in wheat canopies in the field
by: Burgess, Alexandra J., et al.
Published: (2015)
by: Burgess, Alexandra J., et al.
Published: (2015)
Towards low-cost image-based plant phenotyping using reduced-parameter CNN
by: Atanbori, John, et al.
Published: (2018)
by: Atanbori, John, et al.
Published: (2018)
Field phenotyping for the future
by: Atkinson, Jonathan A., et al.
Published: (2018)
by: Atkinson, Jonathan A., et al.
Published: (2018)
AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping
by: Pound, Michael P., et al.
Published: (2017)
by: Pound, Michael P., et al.
Published: (2017)
Large pose 3D face reconstruction from a single image via direct volumetric CNN regression
by: Jackson, Aaron S., et al.
Published: (2017)
by: Jackson, Aaron S., et al.
Published: (2017)
The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology
by: Burrell, Thomas, et al.
Published: (2017)
by: Burrell, Thomas, et al.
Published: (2017)
A canopy conundrum: can wind-induced movement help to increase crop productivity by relieving photosynthetic limitations?
by: Murchie, Erik H., et al.
Published: (2019)
by: Murchie, Erik H., et al.
Published: (2019)
Human pose estimation via convolutional part heatmap regression
by: Bulat, Adrian, et al.
Published: (2016)
by: Bulat, Adrian, et al.
Published: (2016)
Convolutional aggregation of local evidence for large pose face alignment
by: Bulat, Adrian, et al.
Published: (2016)
by: Bulat, Adrian, et al.
Published: (2016)
How far are we from solving the 2D & 3D face alignment problem? (and a dataset of 230,000 3D facial landmarks)
by: Bulat, Adrian, et al.
Published: (2017)
by: Bulat, Adrian, et al.
Published: (2017)
Binarized convolutional landmark localizers for human pose estimation and face alignment with limited resources
by: Bulat, Adrian, et al.
Published: (2017)
by: Bulat, Adrian, et al.
Published: (2017)
Super-FAN: integrated facial landmark localization and super-resolution of real-world low resolution faces in arbitrary poses with GANs
by: Bulat, Adrian, et al.
Published: (2018)
by: Bulat, Adrian, et al.
Published: (2018)
Exploring relationships between canopy architecture, light distribution and photosynthesis in contrasting rice genotypes using 3D canopy reconstruction
by: Burgess, Alexandra J., et al.
Published: (2017)
by: Burgess, Alexandra J., et al.
Published: (2017)
Quantitative definition of phenotypic variation in land snail shells
by: Jackson, H
Published: (2022)
by: Jackson, H
Published: (2022)
Leaf energy balance modelling as a tool to infer habitat preference in the early angiosperms
by: Lee, Alexandra P., et al.
Published: (2015)
by: Lee, Alexandra P., et al.
Published: (2015)
Phenotyping root architecture in diverse wheat germplasm
by: Atkinson, Jonathan A.
Published: (2016)
by: Atkinson, Jonathan A.
Published: (2016)
Safety conscious or living dangerously: what is the ‘right’ level of plant photoprotection for fitness and productivity?
by: Murchie, Erik H.
Published: (2017)
by: Murchie, Erik H.
Published: (2017)
Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies
by: Atkinson, Jonathan A., et al.
Published: (2017)
by: Atkinson, Jonathan A., et al.
Published: (2017)
Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies
by: Atkinson, Jonathan A., et al.
Published: (2017)
by: Atkinson, Jonathan A., et al.
Published: (2017)
Novel monitoring systems to obtain dairy cattle phenotypes associated with sustainable production
by: Bell, Matthew J., et al.
Published: (2018)
by: Bell, Matthew J., et al.
Published: (2018)
Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies
by: Retkute, Renata, et al.
Published: (2018)
by: Retkute, Renata, et al.
Published: (2018)
An updated protocol for high throughput plant tissue sectioning
by: Atkinson, Jonathan A., et al.
Published: (2017)
by: Atkinson, Jonathan A., et al.
Published: (2017)
A CNN cascade for landmark guided semantic part segmentation
by: Jackson, Aaron S., et al.
Published: (2016)
by: Jackson, Aaron S., et al.
Published: (2016)
Deep learning for real world face alignment
by: Bulat, Adrian
Published: (2019)
by: Bulat, Adrian
Published: (2019)
Mechanical modelling quantifies the functional importance of outer tissue layers during root elongation and bending
by: Dyson, Rosemary J., et al.
Published: (2014)
by: Dyson, Rosemary J., et al.
Published: (2014)
Leaf segmentation in plant phenotyping: a collation study
by: Scharr, Hanno, et al.
Published: (2016)
by: Scharr, Hanno, et al.
Published: (2016)
Phenotyping: Targeting genotype’s rich cousin for diagnosis
by: Baynam, G., et al.
Published: (2015)
by: Baynam, G., et al.
Published: (2015)
Effect of the extracellular environment on astrocyte phenotype
by: Smith, Z H
Published: (2020)
by: Smith, Z H
Published: (2020)
Root system markup language: toward an unified root architecture description language
by: Lobet, Guillaume, et al.
Published: (2015)
by: Lobet, Guillaume, et al.
Published: (2015)
Similar Items
-
Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
by: Pound, Michael P., et al.
Published: (2017) -
Plant phenotyping: an active vision cell for three-dimensional plant shoot reconstruction
by: Pridmore, Tony P., et al.
Published: (2018) -
Deep learning for multi-task plant phenotyping
by: Pound, Michael P., et al.
Published: (2017) -
A patch-based approach to 3D plant shoot phenotyping
by: Pound, Michael P., et al.
Published: (2016) -
Automated recovery of 3D models of plant shoots from multiple colour images
by: Pound, Michael P., et al.
Published: (2014)