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contribute to the design and development of Machine Vision approaches for the quantitative analysis and phenotyping of agricultural systems: Training/Development of computational models for the quantitative
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multiple-output) for high data rate and reliability, integrates semantic and goal-oriented communication, and leverages physics-informed machine learning. A key innovation will be the development
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