2022
Accelerating image-based plant phenotyping and pattern recognition: deep learning or few-shot learning?
In recent years, deep learning methods have played a great role in the plant sciences and achieved a series of remarkable achievements in many fields. Few-shot learning is a new branch of deep learning, which aims to develop an intelligent model with good generalization from only few data, towards the combination of machine intelligence with flexibility and extensibility. Both deep learning and few-shot learning are technological explorations in the field of plant sciences that have the potential to greatly accelerate their applications.
2021
Deep learning or few-shot learning?
Few-shot learning is a new branch of deep learning, which aims to develop an intelligent model with good generalization from only few data, towards the combination of machine intelligence with flexibility and extensibility. Both deep learning and few-shot learning are technological explorations in the field of plant sciences that have the potential to greatly accelerate their applications.
2018
Plants in computer vision
This collection includes work on plant detection, segmentation and modelling from image data, at many different scales.
2016
Plant genome editing
This series focuses on gene editing as an effective tool in plant biotechnology and genetic engineering.
2014
Plant phenotyping and phenomics
This series covers all aspects of phenotyping and phenomics technologies as applied to plant research and includes and includes a number of invited contributions from speakers at the 3rd International Plant Phenotyping Symposium.
2013
Next Generation Sequencing technologies for plant research
This series focuses on the use of different sequencing technologies that allow us to sequence DNA and RNA much more quickly and cheaply than Sanger sequencing and their application to plant research.