We propose a multi-input multi-output fully convolutional neural network model for MRI synthesis.
The model is robust to missing data, as it benefits from, but does not require, additional …

Counting the number of leaves in plants is important for plant phenotyping, since it can be
used to assess plant growth stages. We propose a learning-based approach for counting …

Phenotyping is important to understand plant biology, but current solutions are costly, not
versatile or are difficult to deploy. To solve this problem, we present Phenotiki, an affordable …

… To quantitatively assess the performance of our approach, we adopt the same evaluation
metrics as in Giuffrida et al. (2015) (now a consensus in the broad community): …

Image-based plant phenotyping has been steadily growing and this has steeply increased
the need for more efficient image analysis techniques capable of evaluating multiple plant …

The synthesis of medical images is an intensity transformation of a given modality in a way
that represents an acquisition with a different modality (in the context of MRI this represents …

Background Image-based plant phenotyping has become a powerful tool in unravelling
genotype–environment interactions. The utilization of image analysis and machine learning …

The phenotypic analysis of root system growth is important to inform efforts to enhance plant
resource acquisition from soils; however, root phenotyping remains challenging because of …

Foundation models are large models pre-trained on tremendous amount of data. They can
be typically adapted to diverse downstream tasks with minimal effort. However, as foundation …

High throughput plant phenotyping is emerging as a necessary step towards meeting
agricultural demands of the future. Central to its success is the development of robust computer …