Advantages of Machine Learning in Image Recognition and Detection

Abstract

Now that artificial intelligence is widely used, machine learning, as an emerging branch of computer science, has shown great potential, especially in the field of image recognition and detection. Therefore, this paper hopes to explore and summarize the advantages and disadvantages of machine learning in this field, to provide constructive guidance for relevant practitioners. This paper examines papers in many related fields and summarizes how convolutional neural networks and deep learning technologies have revolutionized image processing applications from medical imaging to autonomous vehicles. Key benefits include automation that can identify complex patterns with high accuracy, reduce human error and speed up analysis, and adaptability to ever-changing data. It also addresses major challenges facing machine learning today, such as data quality and quantity issues, the "black box" nature of deep learning models, and privacy concerns. To sum up, although machine learning has many advantages, it also has many problems brought by the nature of its own algorithm that need to be solved. Finally, by studying the advantages and limitations of machine learning, this paper hopes to provide a reference for researchers in this field.