Application of Machine Learning in Image Segmentation of Metal Microstructures
The application of machine learning in image analysis of metal microstructures was introduced,and also the development process of microstructures was reviewed.Particularly,these applications such as traditional machine learning method,deep learning method and large-scale model in microstructure image segmentation were mainly introduced,and then detailed summary and illustrative examples were carried out.Among these methods,the deep learning method could automatically extract high-dimensional features,quickly and accurately segment a batch of images.However,this method had some shortcomings such as strong data dependence and poor universality,which limited the popularization and application of this method to a certain extent.The emergence of large-scale models provided a new solution for the lack of generalization ability and excessive dependence on data.And then,by analyzing the applications of large models in the segmentation of metal microstructure images,the rich application prospect of large models in the field of metal materials was pointed out,and the main development direction of large-scale models in the future was discussed.
artificial intelligenceimage segmentationmicrostructuredeep learninglarge-scale model
万方数据
维普
