In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

Deep learning proved its efficiency in many fields of computer science such as computer
vision, image classifications, object detection, image segmentation, and more. Deep …

You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

Plant phenotype plays an important role in genetics, botany, and agronomy, while the
currently popular methods for phenotypic trait measurement have some limitations in …

Plant phenoty** has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …

Deep learning (DL), a subset of machine learning approaches, has emerged as a versatile
tool to assimilate large amounts of heterogeneous data and provide reliable predictions of …

A lot of hype has recently been generated around deep learning, a novel group of artificial
intelligence approaches able to break accuracy records in pattern recognition. Over the …

Breeding crops for high yield and superior adaptability to new and variable climates is
imperative to ensure continued food security, biomass production, and ecosystem services …

Analyzing medical data to find abnormalities is a time-consuming and costly task,
particularly for rare abnormalities, requiring tremendous efforts from medical experts …

Advances in high‐throughput omics technologies are leading plant biology research into the
era of big data. Machine learning (ML) performs an important role in plant systems biology …