ترجمه تخصصی انگلیسی

In today’s world, where an immense volume of data is generated and stored by digital devices, processing this data and extracting valuable insights from it is a fundamental necessity. One of the widespread approaches for this purpose is employing machine learning models.

In this realm, data preprocessing techniques have garnered significant attention as a fundamental stage. Data preprocessing encompasses stages such as cleansing, transformation, and feature extraction to prepare the data for input into machine learning models.

In this research, the impact of applying various data preprocessing techniques on the performance of machine learning models in object detection in images has been investigated. The results demonstrate that employing an appropriate combination of data preprocessing techniques can lead to a substantial improvement in the accuracy and efficiency of the models in detecting objects in images.