Review of the latest 2022 research on "deep learning methods for industrial defect detection"

Thesis link ：http://scis.scichina.com/ssi2022.html#526

The industrial defect detection method based on deep learning can reduce the cost of traditional manual quality inspection , Improve the accuracy and efficiency of detection , Therefore, it plays an important role in Intelligent Manufacturing , And gradually become one of the emerging research hotspots in the field of computer vision . It is widely used No one can inspect 、 Intelligent inspection 、 In various production and operation and maintenance scenarios such as quality control . The purpose of this review is to define the task of industrial defect detection 、 difficulty 、 Challenge 、 The mainstream approach 、 Public data sets and evaluation indicators are comprehensively summarized , To help researchers quickly understand the field . have In general , This paper first introduces the background and characteristics of industrial defect detection . next , Mark the situation according to the actual data , The defect mode has been divided know 、 The defect mode is unknown and a few defects are marked 3 Research task settings , Further induction and analysis are made according to the type of method , Discussed Performance advantages and disadvantages of each method and applicable scenarios , The relevance between the method and the actual application requirements is clarified . Besides , This paper also summarizes the method deployment Key auxiliary technologies in , The limitations of the existing methods in the actual industrial implementation are summarized . Last , This article is about the future development of this field The development trend and potential research direction are prospected .