Open AccessImage Acquisition Time Series Prediction Method Based on Deep Learning
Author(s) -
Zhisong Mo,
Yifei Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1848/1/012080
Subject(s) - series (stratigraphy) , artificial intelligence , computer science , time series , deep learning , artificial neural network , image (mathematics) , machine learning , pattern recognition (psychology) , sequence (biology) , paleontology , genetics , biology
At present, in-depth learning can be said to be a learning method based on neural network, and time series can be used to achieve prediction results. Therefore, a time series prediction method for image collection based on deep learning is proposed. Based on time series prediction, the image collection in deep learning is analyzed, and the DBN model is combined with GCRBM model to train the model, identify the time series category, and reconstruct the sequence in order to achieve complete time series prediction. The experimental results show that the time series prediction method works well.