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).
I hope you all are doing well during this difficult time.
As a member of the Edinburgh Plant Science community, I have written a blog post on the importance of data and code sharing in research.
I hope it is of your interest: http://www.edinburghplantscience.co.uk/blog/science-benefitting-data-an…
PhD on Neural Network Architecture Optimisation
PhD on Domain Adaptation in Federated Learning
Special Session in “Deep Learning for Crop Science”
More information at: https://sites.google.com/alumni.imtlucca.it/deep-learning-for-crop-science
My new journal paper “UNSUPERVISED ROTATION FACTORIZATION IN RESTRICTED BOLTZMANN MACHINES” is now available at HTTPS://IEEEXPLORE.IEEE.ORG/DOCUMENT/8870198. This paper shows a new method to learn rotation-invariant features on shallow neural network, without the necessity to use data augmentation. The paper shows mathematical and experimental proofs of its effectiveness.
I have now moved from the UoE to the Napier university as Lecturer in Data Science.