Practice and Optimization of Image Recognition Technology for Higher Vocational Computer Application Majors Based on Deep Learning: Taking Industrial Product Defect Detection as an Example

Abstract

This article focuses on the field of computer application majors in higher vocational and technical colleges. It deeply expounds on the case applications of deep learning and related technologies in image recognition technology, centering around the actual enterprise requirements and technological requirements of industrial product defect detection. By building different deep  learning models and related technologies, this article collects product image data in enterprise production, thus completing training, testing, and evaluation. Secondly, it compares the differences of each model in key indicators such as detection accuracy and recall rate, and combines with chart analysis to visually display the changes of the loss function and the accuracy improvement curve during the model training process. The design and analysis of the case can effectively enhance the practical operation and technical application abilities of higher vocational students in image recognition technology, and also provide case support for exchanges among industry practitioners.