One of the major global challenges that can be addressed by deep learning computing is food security.
“Plant phenotyping is leading the studies to help researchers invent ways to overcome this challenge. The use of deep learning in plant phenotyping has opened a new era for researchers. They are developing advanced and accurate systems to improve crop yield and crop management,” said Mostafa.
The research analyzes the way deep learning models work by first identifying problems that developers face when building them. Mostafa noted that sometimes the deep learning models perform extremely well for experimental data, but due to the complex data processing operations, fail to perform similarly in real-life situations.Article content
As deep learning-based models become more involved in automation, monitoring, and decision-making tasks, Mostafa said the research findings may also contribute to the use of these systems in health care, mining, law enforcement, precision agriculture, and other industries.
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