We are looking for two Senior Software Engineers that will contribute to the PhenomUK-RI: The UK Plant & Crop Phenotyping Infrastructure within the Institute for Digital Communications at the University of Edinburgh, which is funded by UKRI/BBSRC in collaboration with colleagues at The University of Nottingham and other University partners Read more…
We are looking for one enthusiastic PhD student to work on a cross-disciplinary project within the AI Doctoral Training Centre at the University of Nottingham (UK). This call is for home applicants only. Click here for more information about the call. Click here for more information about the Faculty of Read more…
Image-based plant analysis for sustainable agriculture Image-based plant phenotyping allows the quantification of traits (e.g. leaf area, number, colour) reflecting plant performance non-destructively. This approach helps in deciphering the complex genetic-environment interactions influencing its performance and finding the best-adapted crop varieties to local environmental constraints for sustainable agriculture. Deep learning Read more…
I am looking for a PhD student for the 3-year project entitled “Semi-Supervised, Unsupervised, and Self-Supervised Transfer Learning for Computer Vision”. Transfer learning has been demonstrated to improve the generalisation of deep neural networks to real-world applications, especially in situations where labelled training sets are missing. Current proposed methods work Read more…
I am pleased to communicate that the research topic (special issue) “Synthetic Data for Computer Vision in Agriculture” is now open for submission. This research topic is in the Frontiers in Plant Science journal (Impact Factor 5.7). More information is available at https://www.frontiersin.org/research-topics/29199/synthetic-data-for-computer-vision-in-agriculture. You are invited to submit your original Read more…
Plant phenotyping is the identification of effects on plant structure and function (the phenotype) resulting from genotypic differences (i.e., differences in the genetic code) and the environmental conditions a plant has been exposed to. Knowledge of plant phenotypes is a key ingredient of the knowledge-based bioeconomy, which not only literally Read more…
Machine learning (ML) has been recognized as central to artificial intelligence (AI) for many decades. The question of how the things that have been learned in one context can be re-used and adapted in other related contexts, however, has only been brought to the attention of the wider ML research Read more…
I am delighted to inform you that I am one of the guest editors for the Special Issue “Acquire and Perceive: Novel Approaches for Imaging-based Plant Phenotyping” on Remote Sensing (MPDI).
PhD on Neural Network Architecture Optimisation
PhD on Domain Adaptation in Federated Learning