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Caterpillars are significant pests in agriculture, causing substantial damage to crops. Traditional methods for detecting and tracking caterpillars are time-consuming and often ineffective. This paper proposes a novel approach using video filtering techniques to detect and track caterpillars. We present a system that utilizes computer vision and machine learning algorithms to identify and track caterpillars in video footage. Our approach, called Video Filtrado de la Oruga (VFO), demonstrates high accuracy and efficiency in detecting and tracking caterpillars, making it a promising tool for agricultural monitoring and pest control. video filtrado de la oruga best
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