Outputs (36)

Addressing multiple salient object detection via dual-space long-range dependencies (2023)
Journal Article
Deng, B., French, A. P., & Pound, M. P. (2023). Addressing multiple salient object detection via dual-space long-range dependencies. Computer Vision and Image Understanding, 235, Article 103776. https://doi.org/10.1016/j.cviu.2023.103776

Salient object detection plays an important role in many downstream tasks. However, complex real-world scenes with varying scales and numbers of salient objects still pose a challenge. In this paper, we directly address the problem of detecting multi... Read More about Addressing multiple salient object detection via dual-space long-range dependencies.

Root architecture and leaf photosynthesis traits and associations with nitrogen-use efficiency in landrace-derived lines in wheat (2022)
Journal Article
Kareem, S. H., Hawkesford, M. J., DeSilva, J., Weerasinghe, M., Wells, D. M., Pound, M. P., …Foulkes, M. J. (2022). Root architecture and leaf photosynthesis traits and associations with nitrogen-use efficiency in landrace-derived lines in wheat. European Journal of Agronomy, 140, Article 126603. https://doi.org/10.1016/j.eja.2022.126603

Root system architecture (RSA) is important in optimizing the use of nitrogen. High-throughput phenotyping techniques may be used to study root system architecture traits under controlled environments. A root phenotyping platform, consisting of germi... Read More about Root architecture and leaf photosynthesis traits and associations with nitrogen-use efficiency in landrace-derived lines in wheat.

A review of ultrasonic sensing and machine learning methods to monitor industrial processes (2022)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2022). A review of ultrasonic sensing and machine learning methods to monitor industrial processes. Ultrasonics, 124, Article 106776. https://doi.org/10.1016/j.ultras.2022.106776

Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved general... Read More about A review of ultrasonic sensing and machine learning methods to monitor industrial processes.

Identification of QTL and underlying genes for root system architecture associated with nitrate nutrition in hexaploid wheat (2022)
Journal Article
GRIFFITHS, M., ATKINSON, J. A., Gardiner, L. J., SWARUP, R., POUND, M. P., WILSON, M. H., …WELLS, D. M. (2022). Identification of QTL and underlying genes for root system architecture associated with nitrate nutrition in hexaploid wheat. Journal of Integrative Agriculture, 21(4), 917-932. https://doi.org/10.1016/s2095-3119%2821%2963700-0

The root system architecture (RSA) of a crop has a profound effect on the uptake of nutrients and consequently the potential yield. However, little is known about the genetic basis of RSA and resource adaptive responses in wheat (Triticum aestivum L.... Read More about Identification of QTL and underlying genes for root system architecture associated with nitrate nutrition in hexaploid wheat.

X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil (2022)
Journal Article
Griffiths, M., Mellor, N., Sturrock, C. J., Atkinson, B. S., Johnson, J., Mairhofer, S., …Wells, D. M. (2022). X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil. Plant Phenome Journal, 5(1), Article e20036. https://doi.org/10.1002/ppj2.20036

The spatial arrangement of the root system, termed root system architecture, is important for resource acquisition as it directly affects the soil zone explored. Methods for phenotyping roots are mostly destructive, which prevents analysis of roots o... Read More about X-ray CT reveals 4D root system development and lateral root responses to nitrate in soil.

A fusion spatial attention approach for few-shot learning (2021)
Journal Article
Song, H., Deng, B., Pound, M., Özcan, E., & Triguero, I. (2022). A fusion spatial attention approach for few-shot learning. Information Fusion, 81, 187-202. https://doi.org/10.1016/j.inffus.2021.11.019

Few-shot learning is a challenging problem in computer vision that aims to learn a new visual concept from very limited data. A core issue is that there is a large amount of uncertainty introduced by the small training set. For example, the few image... Read More about A fusion spatial attention approach for few-shot learning.

Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation (2021)
Journal Article
Bowler, A. L., Pound, M. P., & Watson, N. J. (2021). Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation. Fermentation, 7(4), Article 253. https://doi.org/10.3390/fermentation7040253

Beer fermentation processes are traditionally monitored through sampling and off-line wort density measurements. In-line and on-line sensors would provide real-time data on the fermentation progress whilst minimising human involvement, enabling ident... Read More about Domain adaptation and federated learning for ultrasonic monitoring of beer fermentation.

Convolutional feature extraction for process monitoring using ultrasonic sensors (2021)
Journal Article
Bowler, A., Pound, M., & Watson, N. (2021). Convolutional feature extraction for process monitoring using ultrasonic sensors. Computers and Chemical Engineering, 155, Article 107508. https://doi.org/10.1016/j.compchemeng.2021.107508

Ultrasonic sensors are a low-cost and in-line technique and can be combined with machine learning for industrial process monitoring. However, training accurate machine learning models for process monitoring using sensor data is dependant on the featu... Read More about Convolutional feature extraction for process monitoring using ultrasonic sensors.

Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning (2021)
Journal Article
Bowler, A., Escrig, J., Pound, M., & Watson, N. (2021). Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning. Fermentation, 7(1), Article 34. https://doi.org/10.3390/fermentation7010034

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultraso... Read More about Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning.

Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning (2020)
Journal Article
Khan, F. A., Voß, U., Pound, M. P., & French, A. P. (2020). Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning. Frontiers in Plant Science, 11, Article 1275. https://doi.org/10.3389/fpls.2020.01275

© Copyright © 2020 Khan, Voß, Pound and French. Understanding plant growth processes is important for many aspects of biology and food security. Automating the observations of plant development—a process referred to as plant phenotyping—is increasing... Read More about Volumetric Segmentation of Cell Cycle Markers in Confocal Images Using Machine Learning and Deep Learning.

Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks (2020)
Journal Article
Soltaninejad, M., Sturrock, C. J., Griffiths, M., Pridmore, T. P., & Pound, M. P. (2020). Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks. IEEE Transactions on Image Processing, 29, 6667-6679. https://doi.org/10.1109/TIP.2020.2992893

© 1992-2012 IEEE. We address the complex problem of reliably segmenting root structure from soil in X-ray Computed Tomography (CT) images. We utilise a deep learning approach, and propose a state-of-the-art multi-resolution architecture based on enco... Read More about Three Dimensional Root CT Segmentation Using Multi-Resolution Encoder-Decoder Networks.

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.

Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking (2019)
Journal Article
Gibbs, J. A., Burgess, A. J., Pound, M. P., Pridmore, T. P., & Murchie, E. H. (2019). Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking. Plant Physiology, 181, 28-42. https://doi.org/10.1104/pp.19.00141

Understanding the relationships between local environmental conditions and plant structure and function is critical for both fundamental science and for improving the performance of crops in field settings. Wind-induced plant motion is important in m... Read More about Recovering Wind-induced Plant motion in Dense Field Environments via Deep Learning and Multiple Object Tracking.

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.

Identification of nitrogen-dependent QTL and underlying genes for root system architecture in hexaploid wheat (2019)
Other
Griffiths, M., Atkinson, J. A., Gardiner, L., Swarup, R., Pound, M. P., Wilson, M. H., …Wells, D. M. (2019). Identification of nitrogen-dependent QTL and underlying genes for root system architecture in hexaploid wheat

The root system architecture (RSA) of a crop has a profound effect on the uptake of nutrients and consequently the potential yield. However, little is known about the genetic basis of RSA and resource dependent response in wheat (Triticum aestivum L.... Read More about Identification of nitrogen-dependent QTL and underlying genes for root system architecture in hexaploid wheat.

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.

Uncovering the hidden half of plants using new advances in root phenotyping (2018)
Journal Article
Atkinson, J. A., Pound, M. P., Bennett, M. J., & Wells, D. M. (2019). Uncovering the hidden half of plants using new advances in root phenotyping. Current Opinion in Biotechnology, 55, 1-8. https://doi.org/10.1016/j.copbio.2018.06.002

© 2018 The Authors Major increases in crop yield are required to keep pace with population growth and climate change. Improvements to the architecture of crop roots promise to deliver increases in water and nutrient use efficiency but profiling the r... Read More about Uncovering the hidden half of plants using new advances in root phenotyping.

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.

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.

Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems (2017)
Journal Article
Burgess, A. J., Retkute, R., Pound, M. P., Mayes, S., & Murchie, E. H. (2017). Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems. Annals of Botany, 119(4), 517-532. https://doi.org/10.1093/aob/mcw242

Background and Aims: Intercropping systems contain two or more species simultaneously in close proximity. Due to contrasting features of the component crops, quantification of the light environment and photosynthetic productivity is extremely difficu... Read More about Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems.

The 4-Dimensional Plant: Effects of Wind-Induced Canopy Movement on Light Fluctuations and Photosynthesis (2016)
Journal Article
Burgess, A. J., Retkute, R., Preston, S. P., Jensen, O. E., Pound, M. P., Pridmore, T. P., & Murchie, E. H. (2016). The 4-Dimensional Plant: Effects of Wind-Induced Canopy Movement on Light Fluctuations and Photosynthesis. Frontiers in Plant Science, 7(1392), https://doi.org/10.3389/fpls.2016.01392

Physical perturbation of a plant canopy brought about by wind is a ubiquitous phenomenon and yet its biological importance has often been overlooked. This is partly due to the complexity of the issue at hand: wind-induced movement (or mechanical exci... Read More about The 4-Dimensional Plant: Effects of Wind-Induced Canopy Movement on Light Fluctuations and Photosynthesis.

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.

Three-dimensional reconstruction of plant shoots from multiple images using an active vision system (2015)
Journal Article
Gibbs, J., Pound, M. P., Wells, D. M., Murchie, E. H., French, A. P., & Pridmore, T. P. (2015). Three-dimensional reconstruction of plant shoots from multiple images using an active vision system

The reconstruction of 3D models of plant shoots is a challenging problem central to the emerging discipline of plant phenomics – the quantitative measurement of plant structure and function. Current approaches are, however, often limited by the use o... Read More about Three-dimensional reconstruction of plant shoots from multiple images using an active vision system.

High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field (2015)
Journal Article
Burgess, A. J., Retkute, R., Pound, M. P., Foulkes, J., Preston, S. P., Jensen, O. E., …Murchie, E. H. (2015). High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field. Plant Physiology, 169(2), 1192-1204. https://doi.org/10.1104/pp.15.00722

Photoinhibition reduces photosynthetic productivity; however, it is difficult to quantify accurately in complex canopies partly because of a lack of high-resolution structural data on plant canopy architecture, which determines complex fluctuations o... Read More about High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field.

Root system markup language: Toward a unified root architecture description language (2015)
Journal Article
Meunier, F., Lobet, G., Pound, M. P., Diener, J., Pradal, C., Draye, X., …Schnepf, A. (2015). Root system markup language: Toward a unified root architecture description language. Plant Physiology, 167(3), 617-627. https://doi.org/10.1104/pp.114.253625

© 2015 American Society of Plant Biologists. All rights reserved. The number of image analysis tools supporting the extraction of architectural features of root systems has increased in recent years. These tools offer a handy set of complementary fac... Read More about Root system markup language: Toward a unified root architecture description language.

Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat (2015)
Journal Article
Atkinson, J. A., Wingen, L. U., Griffiths, M., Pound, M. P., Gaju, O., Foulkes, M. J., …Wells, D. M. (2015). Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat. Journal of Experimental Botany, 66(8), 2283-2292. https://doi.org/10.1093/jxb/erv006

Seedling root traits of wheat (Triticum aestivum L.) have been shown to be important for efficient establishment and linked to mature plant traits such as height and yield. A root phenotyping pipeline, consisting of a germination paper-based screen c... Read More about Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat.

Quantification of Fluorescent Reporters in Plant Cells (2014)
Book Chapter
Pound, M., French, A. P., & Wells, D. M. (2015). Quantification of Fluorescent Reporters in Plant Cells. In J. M. Estevez (Ed.), Plant Cell Expansion: Methods and Protocols (123-131). Springer. https://doi.org/10.1007/978-1-4939-1902-4_11

© Springer Science+Business Media New York 2015. Fluorescent reporters are powerful tools for plant research. Many studies require accurate determination of fluorescence intensity and localization. Here, we describe protocols for the quantification o... Read More about Quantification of Fluorescent Reporters in Plant Cells.

Quantification of fluorescent reporters in plant cells (2014)
Book Chapter
Pound, M., French, A. P., & Wells, D. M. (2014). Quantification of fluorescent reporters in plant cells. In Plant Cell Expansion: Methods and Protocols (123--131). Springer. https://doi.org/10.1007/978-1-4939-1902-4

Automated recovery of 3D models of plant shoots from multiple colour images (2014)
Journal Article
Pound, M. P., French, A. P., Murchie, E. H., & Pridmore, T. P. (2014). Automated recovery of 3D models of plant shoots from multiple colour images. Plant Physiology, 166(4), https://doi.org/10.1104/pp.114.248971

Increased adoption of the systems approach to biological research has focussed attention on the use of quantitative models of biological objects. This includes a need for realistic 3D representations of plant shoots for quantification and modelling.... Read More about Automated recovery of 3D models of plant shoots from multiple colour images.

Systems Analysis of Auxin Transport in the Arabidopsis Root Apex (2014)
Journal Article
Band, L. R., Wells, D. M., Fozard, J. A., Ghetiu, T., French, A. P., Pound, M. P., …Bennett, M. J. (2014). Systems Analysis of Auxin Transport in the Arabidopsis Root Apex. Plant Cell, 26(3), 862-875. https://doi.org/10.1105/tpc.113.119495

Auxin is a key regulator of plant growth and development. Within the root tip, auxin distribution plays a crucial role specifying developmental zones and coordinating tropic responses. Determining how the organ-scale auxin pattern is regulated at the... Read More about Systems Analysis of Auxin Transport in the Arabidopsis Root Apex.

RootNav: navigating images of complex root architectures (2013)
Journal Article
Pound, M. P., French, A. P., Atkinson, J. A., Wells, D. M., Bennett, M. J., & Pridmore, T. (2013). RootNav: navigating images of complex root architectures. Plant Physiology, 162(4), 1802-1814. https://doi.org/10.1104/pp.113.221531

We present a novel image analysis tool that allows the semiautomated quantification of complex root system architectures in a range of plant species grown and imaged in a variety of ways. The automatic component of RootNav takes a top-down approach,... Read More about RootNav: navigating images of complex root architectures.