These studies collectively illustrate the evolution of deep-learning-based goose-behavior recognition—from individual detection to multi-class behavioral classification and health assessment—accompanied by a clear trend from reliance on high-performance computing platforms toward embedded-edge deployment, thereby advancing the practical realization of precision farming in the goose industry.
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DAEF-YOLO Model for Individual and Behavior Recognition of Sanhua Geese in Precision Farming Applications.
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