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Machine Learning-based Object Recognition Technology for Bird Identification System

机译:基于机器学习的鸟类识别系统目标识别技术

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The object recognition system for machine learning has become widely known recently, and each algorithm of the object recognition system has its own advantages and disadvantages. The disadvantages are that the speed of identification is slow and the accuracy of identification is poor. The purpose of this paper is to identify birds through the YOLO and Custom Vision algorithms. When the user uploads bird photos to the two systems through a smart mobile device, the system will identify the objects according to the algorithm. It judges which bird it may be and, after a final comparison, the result with a higher percentage of accuracy is transmitted back to the user, thereby improving the accuracy of the identification system.
机译:用于机器学习的对象识别系统最近已众所周知,对象识别系统的每种算法具有其自身的优点和缺点。缺点是识别速度慢,识别的准确性差。本文的目的是通过YOLO和自定义视觉算法识别鸟类。当用户通过智能移动设备将鸟照片上传到两个系统时,系统将根据算法识别对象。它判断它可能是并且在最终比较之后,将具有较高百分比精度的结果返回给用户,从而提高了识别系统的准确性。

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