Journal
PATTERNS
Volume 2, Issue 9, Pages -Publisher
CELL PRESS
DOI: 10.1016/j.patter.2021.100323
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Funding
- EU FP7 project WATBIO [311929]
- EU [739514]
- Italian Ministry of University and Research Brain Gain Professorship
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High-throughput image-based technologies are being widely used in digital phenomics, with artificial intelligence playing a crucial role in turning vast data into valuable predictions. Specialized programming skills and a deep understanding of machine learning algorithms are necessary for utilizing these technologies. This tutorial systematically reviews tools, technologies, and services available for phenomics data analysis in explainable AI applications.
High-throughput image-based technologies are now widely used in the rapidly developing field of digital phenomics and are generating ever-increasing amounts and diversity of data. Artificial intelligence (AI) is becoming a game changer in turning the vast seas of data into valuable predictions and insights. However, this requires specialized programming skills and an in-depth understanding of machine learning, deep learning, and ensemble learning algorithms. Here, we attempt to methodically review the usage of different tools, technologies, and services available to the phenomics data community and show how they can be applied to selected problems in explainable AI-based image analysis. This tutorial provides practical and useful resources for novices and experts to harness the potential of the phenomic data in explainable AI-led breeding programs.
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