<ul><li>Monitoring cattle feeding behavior is crucial for efficient herd management and optimal resource utilization in grazing cattle.</li><li>The ability to automatically recognize feeding events in animals through jaw movement identification can lead to improved diet formulation and early detection of health issues.</li><li>A novel deep neural network model has been introduced in this work, combining acoustic and inertial signals through feature-level fusion.</li><li>The proposed model outperformed traditional and deep learning approaches with an F1-score value of 0.802, representing a 14% increase compared to previous methods.</li></ul>

A multi-head deep fusion model for recognition of cattle foraging events using sound and movement signals

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