计算机深度学习在视觉目标检测中的应用

The Application of Computer Deep Learning in Visual Object Detection

深度学习模型通过学习大量标注的图像数据,能够自动提取图像中的特征,并识别出不同的目标,可以在各种实际场景中实现准确和高效的目标检测。文章以零件缺陷检测的算法为例,介绍了计算机深度学习在视觉目标检测中的处理的流程,并对其局限性进行了分析,并提出解决方案。

By learning from annotated image data,deep learning models can automatically extract features and identify objects,enabling accurate and efficient detection in various real-world scenarios.This article focuses on the algorithm for part defect detection,explaining the process of computer deep learning in visual object detection and the limitations of the analysis,and proposed solutions.