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In order to better implement the whole process of intelligent manufacturing for electronic enterprises in industry 4.0 era, the machine vision is introduced to address the diversity problem of deficiency on defects in the ability of algorithms. Firstly, through depth learning for the small labeled sample datasets a feature model is obtained. After that, we train the feature model for implement the LED screen inspection by transfer learning. Meanwhile, using incremental learning the parameters of model are corrected step by step. Finally, the FCNet (Fully Connected Neural Network) is used to implement the classification. This paper discussed machine vision to complete LED TV screen detection, and the incremental learning model of the sample datasets is given as a continuous supplement. Many experiments show that the deep learning could further improve the accuracy on automatic inspection, also enhance the flexibility and intelligence level on industrial production, and expand the application of machine vision to provide demonstration.