Semi supervised inspection algorithm of automatic packaging curve based on deep learning

Article type: Research Article

Authors: He, Yong

Affiliations: Chongqing Chemical Industry Vocational College, Chongqing 400020, China | E-mail: [email protected]

Correspondence: [*] Corresponding author: Chongqing Chemical Industry Vocational College, Chongqing 400020, China. E-mail: [email protected].

Abstract: The current automatic packaging process is complex, requires high professional knowledge, poor universality, and difficult to apply in multi-objective and complex background. In view of this problem, automatic packaging optimization algorithm has been widely paid attention to. However, the traditional automatic packaging detection accuracy is low, the practicability is poor. Therefore, a semi-supervised detection method of automatic packaging curve based on deep learning and semi-supervised learning is proposed. Deep learning is used to extract features and posterior probability to classify unlabeled data. KDD CUP99 data set was used to verify the accuracy of the algorithm. Experimental results show that this method can effectively improve the performance of automatic packaging curve semi-supervised detection system.

Keywords: Deep learning, automated packaging curve, semi supervised, detection algorithm

DOI: 10.3233/JCM-215690

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 2, pp. 363-372, 2022