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 Read more…
I am organising this PhenomUK funded workshop – date 9th March 2022. This is going to be an in-person full-day event held within the Edinburgh Zoo. Participation in the workshop is free.More information (and how to participate) here: https://www.phenomuk.net/event/ai-for-plant-image-analysis-where-we-are-and-whats-next-full-day-workshop/
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 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 Read more…
It took a while, but I finally managed to complete my new website. It contains the same information of the previous one, but presented in a better template. I have updated all the news and whatnots. I am happy that 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 Read more…
This workshop plans to showcase the challenges raised by working on computer vision for plant phenotyping and agriculture. Workshop goals include demonstrating the state-of-the-art, identifying key unsolved problems, and introducing computer scientists with an interest in plant phenotyping to the 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 Read more…
I am delighted to inform you all that I’ve been invited to give a talk at the JST Workshop in Japan (although held virtually given the current circumstances). The title of my talk is “Deep Learning for Plant Image Analysis“. 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).