An object identification system finds real-world pairings using photographs of the world with pre-defined object models. With the ever-growing volume of digital photographs in public and private databases, there is an increasing demand for robust object recognition systems. While humans can identify objects easily, robots find it challenging, yet it is crucial for their autonomy. Object recognition technologies, a key field in robotics using computer vision (CV) and machine learning (ML), are essential for enhancing robotic capabilities. This study focuses on applying current object identification algorithms and methods to drone imagery. Drones offer unique advantages, such as closer proximity to objects and top-down perspective angles, although these benefits also introduce challenges, such as integrating deep learning systems for compute-intensive processes. Ensuring maximum visibility during drone navigation is crucial for effective object identification.
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