Background:
As known that the semi-supervised algorithm is a classical algorithm in semi-supervised learning
algorithm.
Methods:
In the paper, it proposed improved cooperative semi-supervised learning algorithm, and the algorithm process is
presented in detailed, and it is adopted to predict unlabeled electronic components image.
Results:
In the experiments of classification and recognition of electronic components, it show that through the method
the accuracy the proposed algorithm in electron device image recognition can be significantly improved, the improved
algorithm can be used in the actual recognition process .
Conclusion:
With the continuous development of science and technology, machine vision and deep learning will play a
more important role in people's life in the future. The subject research based on the identification of the number of
components is bound to develop towards the direction of high precision and multi-dimension, which will greatly improve
the production efficiency of electronic components industry.
Guest Editorial: Special Section on Advanced Deep Learning Algorithms for Industrial Internet of Things
